XPRScontrol Enumeration

Namespace: Optimizer
Assembly: xprsdn (in xprsdn.dll) Version: 45.01.02+1f9fd7ff9a8620394fec1839699751312debed40

Syntax

public enum XPRScontrol

Members

Member name	Value	Description
MPSRHSName	6,001	When reading an MPS file, this control determines which entries from the RHS section will be read. As with all string controls, this is of length 64 characters plus a null terminator, \0.
MPSObjName	6,002	When reading an MPS file, this control determines which neutral row will be read as the objective function. If this control is set when reading a multi-objective MPS file, only the named objective will be read; all other objectives will be ignored. As with all string controls, this is of length 64 characters plus a null terminator, \0.
MPSRangeName	6,003	When reading an MPS file, this control determines which entries from the RANGES section will be read. As with all string controls, this is of length 64 characters plus a null terminator, \0.
MPSBoundName	6,004	When reading an MPS file, this control determines which entries from the BOUNDS section will be read. As with all string controls, this is of length 64 characters plus a null terminator, \0.
OutputMask	6,005	Mask to restrict the row and column names written to file. As with all string controls, this is of length 64 characters plus a null terminator, \0.
TunerMethodFile	6,017	Tuner: Defines a file from which the tuner can read user-defined tuner method.
TunerOutputPath	6,018	Tuner: Defines a root path to which the tuner writes the result file and logs.
TunerSessionName	6,019	Tuner: Defines a session name for the tuner.
ComputeExecService	6,022	Selects the Insight execution service that will be used for solving remote optimizations.
Msp_DuplicateSolutionsPolicy	6,203
Msp_DefaultUserSolFeasTol	6,209
Msp_DefaultUserSolMipTol	6,210
Msp_IncludeProbNameInLogging	6,211
Msp_WriteSlxSolLogging	6,212
Msp_EnableSlackStorage	6,213
Msp_OutputLog	6,214
Msp_Sol_FeasTol	6,402
Msp_Sol_MipTol	6,403
Msp_Sol_BitFieldsUsr	6,406
Mse_CallbackCullSols_MipObject	6,601
Mse_CallbackCullSols_Diversity	6,602
Mse_CallbackCullSols_ModObject	6,603
Mse_OptimizeDiversity	6,607
Mse_OutputTol	6,609
Mse_OutputLog	6,610
MatrixTol	7,001	The zero tolerance on matrix elements. If the value of a matrix element is less than or equal to MATRIXTOL in absolute value, it is treated as zero. The control applies when solving a problem, for an input tolerance see INPUTTOL.
PivotTol	7,002	Simplex: The zero tolerance for matrix elements. On each iteration, the simplex method seeks a nonzero matrix element to pivot on. Any element with absolute value less than PIVOTTOL is treated as zero for this purpose.
FeasTol	7,003	This tolerance determines when a solution is treated as feasible. If the amount by which a constraint's activity violates its right-hand side or ranged bound is less in absolute magnitude than FEASTOL, then the constraint is treated as satisfied. Similarly, if the amount by which a column violates its bounds is less in absolute magnitude than FEASTOL, those bounds are also treated as satisfied.
OutputTol	7,004	Zero tolerance on print values.
SOSRefTol	7,005	The minimum relative gap between the ordering values of elements in a special ordered set. The gap divided by the absolute value of the larger of the two adjacent values must be at least SOSREFTOL.
OptimalityTol	7,006	Simplex: This is the zero tolerance for reduced costs. On each iteration, the simplex method searches for a variable to enter the basis which has a negative reduced cost. The candidates are only those variables which have reduced costs less than the negative value of OPTIMALITYTOL.
EtaTol	7,007	Tolerance on eta elements. During each iteration, the basis inverse is premultiplied by an elementary matrix, which is the identity except for one column - the eta vector. Elements of eta vectors whose absolute value is smaller than ETATOL are taken to be zero in this step.
RelPivotTol	7,008	Simplex: At each iteration a pivot element is chosen within a given column of the matrix. The relative pivot tolerance, RELPIVOTTOL, is the size of the element chosen relative to the largest possible pivot element in the same column.
MIPTol	7,009	Branch and Bound: This is the tolerance within which a decision variable's value is considered to be integral.
MipTolTarget	7,010	Target MIPTOL value used by the automatic MIP solution refiner as defined by REFINEOPS. Negative and zero values are ignored.
BarPerturb	7,011	Newton barrier: In numerically challenging cases it is often advantageous to apply perturbations on the KKT system to improve its numerical properties. BARPERTURB controlls how much perturbation is allowed during the barrier iterations. By default no perturbation is allowed. Set this parameter with care as larger perturbations may lead to less efficient iterates and the best settings are problem-dependent.
MIPAddCutoff	7,012	Branch and Bound: The amount to add to the objective function of the best integer solution found to give the new CURRMIPCUTOFF. Once an integer solution has been found whose objective function is equal to or better than CURRMIPCUTOFF, improvements on this value may not be interesting unless they are better by at least a certain amount. If MIPADDCUTOFF is nonzero, it will be added to CURRMIPCUTOFF each time an integer solution is found which is better than this new value. This cuts off sections of the tree whose solutions would not represent substantial improvements in the objective function, saving processor time. The control MIPABSSTOP provides a similar function but works in a different way.
MIPAbsCutoff	7,013	Branch and Bound: If the user knows that they are interested only in values of the objective function which are better than some value, this can be assigned to MIPABSCUTOFF. This allows the Optimizer to ignore solving any nodes which may yield worse objective values, saving solution time. When a MIP solution is found a new cut off value is calculated and the value can be obtained from the CURRMIPCUTOFF attribute. The value of CURRMIPCUTOFF is calculated using the MIPRELCUTOFF and MIPADDCUTOFF controls.
MIPRelCutoff	7,014	Branch and Bound: Percentage of the incumbent value to be added to the value of the objective function when an integer solution is found, to give the new value of CURRMIPCUTOFF. The effect is to cut off the search in parts of the tree whose best possible objective function would not be substantially better than the current solution. The control MIPRELSTOP provides a similar functionality but works in a different way.
PseudoCost	7,015	Branch and Bound: The default pseudo cost used in estimation of the degradation associated with an unexplored node in the tree search. A pseudo cost is associated with each integer decision variable and is an estimate of the amount by which the objective function will be worse if that variable is forced to an integral value.
Penalty	7,016	Minimum absolute penalty variable coefficient. BIGM and PENALTY are set by the input routine (readProb (READPROB)) but may be reset by the user prior to lpOptimize (LPOPTIMIZE).
BigM	7,018	The infeasibility penalty used if the "Big M" method is implemented.
MIPAbsStop	7,019	Branch and Bound: The absolute tolerance determining whether the tree search will continue or not. It will terminate if    \|MIPOBJVAL - BESTBOUND\| <= MIPABSSTOP where MIPOBJVAL is the value of the best solution's objective function, and BESTBOUND is the current best solution bound. For example, to stop the tree search when a MIP solution has been found and the Optimizer can guarantee it is within 100 of the optimal solution, set MIPABSSTOP to 100.
MIPRelStop	7,020	Branch and Bound: This determines when the branch and bound tree search will terminate. Branch and bound tree search will stop if:    \|MIPOBJVAL - BESTBOUND\| <= MIPRELSTOP x max(\|BESTBOUND\|,\|MIPOBJVAL\|) where MIPOBJVAL is the value of the best solution's objective function and BESTBOUND is the current best solution bound. For example, to stop the tree search when a MIP solution has been found and the Optimizer can guarantee it is within 5% of the optimal solution, set MIPRELSTOP to 0.05.
CrossoverAccuracyTol	7,023	Newton barrier: This control determines how crossover adjusts the default relative pivot tolerance. When re-inversion is necessary, crossover will compare the recalculated working basic solution with the assumed ones just before re-inversion took place. If the error is above this threshold, crossover will adjust the relative pivot tolerance to address the build-up of numerical inaccuracies.
PrimalPerturb	7,024	The factor by which the problem will be perturbed prior to optimization by primal simplex. A value of 0.0 results in no perturbation prior to optimization. Note the interconnection to the AUTOPERTURB control. If AUTOPERTURB is set to 1, the decision whether to perturb or not is left to the Optimizer. When the problem is automatically perturbed in primal simplex, however, the value of PRIMALPERTURB will be used for perturbation.
DualPerturb	7,025	The factor by which the problem will be perturbed prior to optimization by dual simplex. A value of 0.0 results in no perturbation prior to optimization. Note the interconnection to the AUTOPERTURB control. If AUTOPERTURB is set to 1, the decision whether to perturb or not is left to the Optimizer. When the problem is automatically perturbed in dual simplex, however, the value of DUALPERTURB will be used for perturbation.
BarObjScale	7,026	Defines how the barrier scales the objective.
BarRhsScale	7,027	Defines how the barrier scales the right hand side.
CholeskyTol	7,032	Newton barrier: The tolerance for pivot elements in the Cholesky decomposition of the normal equations coefficient matrix, computed at each iteration of the barrier algorithm. If the absolute value of the pivot element is less than or equal to CHOLESKYTOL, it merits special treatment in the Cholesky decomposition process.
BarGapStop	7,033	Newton barrier and hybrid gradient: This is a convergence parameter, representing the tolerance for the relative duality gap. When the difference between the primal and dual objective function values falls below this tolerance, the Optimizer determines that the optimal solution has been found.
BarDualStop	7,034	Newton barrier and hybrid gradient: This is a convergence parameter, representing the tolerance for dual infeasibilities. If the difference between the constraints and their bounds in the dual problem falls below this tolerance in absolute value, optimization will stop and the current solution will be returned.
BarPrimalStop	7,035	Newton barrier and hybrid gradient: This is a convergence parameter, indicating the tolerance for primal infeasibilities. If the difference between the constraints and their bounds in the primal problem falls below this tolerance in absolute value, the Optimizer will terminate and return the current solution.
BarStepStop	7,036	Newton barrier: A convergence parameter, representing the minimal step size. On each iteration of the barrier algorithm, a step is taken along a computed search direction. If that step size is smaller than BARSTEPSTOP, the Optimizer will terminate and return the current solution.
ElimTol	7,042	The Markowitz tolerance for the elimination phase of the presolve.
MarkowitzTol	7,047	The Markowitz tolerance used for the factorization of the basis matrix.
MIPAbsGapNotify	7,064	Branch and bound: if the gapnotify callback has been set using addCbGapNotify, then this callback will be triggered during the tree search when the absolute gap reaches or passes the value you set of the MIPRELGAPNOTIFY control.
MIPRelGapNotify	7,065	Branch and bound: if the gapnotify callback has been set using addCbGapNotify, then this callback will be triggered during the branch and bound tree search when the relative gap reaches or passes the value you set of the MIPRELGAPNOTIFY control.
BarLargeBound	7,067	Threshold for the barrier to handle large bounds.
PPFactor	7,069	The partial pricing candidate list sizing parameter.
RepairIndefiniteQMax	7,071
BarGapTarget	7,073	Newton barrier: The target tolerance for the relative duality gap. The barrier algorithm will keep iterating until either BARGAPTARGET is satisfied or until no further improvements are possible. In the latter case, if BARGAPSTOP is satisfied, it will declare the problem optimal.
DummyControl	7,075
BarStartWeight	7,076	Newton barrier: This sets a weight for the warm-start point when warm-start is set for the barrier algorithm. Using larger weight gives more emphasis for the supplied starting point.
BarFreeScale	7,077	Defines how the barrier algorithm scales free variables.
SbEffort	7,086	Adjusts the overall amount of effort when using strong branching to select an infeasible MIP entity to branch on.
HeurDiveRandomize	7,089	The level of randomization to apply in the diving heuristic. The diving heuristic uses priority weights on rows and columns to determine the order in which to e.g. round fractional columns, or the direction in which to round them. This control determines by how large a random factor these weights should be changed.
HeurSearchEffort	7,090	Adjusts the overall level of the local search heuristics.
CutFactor	7,091	Limit on the number of cuts and cut coefficients the optimizer is allowed to add to the matrix during tree search. The cuts and cut coefficients are limited by CUTFACTOR times the number of rows and coefficients in the initial matrix.
EigenValueTol	7,097	A quadratic matrix is considered not to be positive semi-definite, if its smallest eigenvalue is smaller than the negative of this value.
IndLinBigM	7,099	During presolve, indicator constraints will be linearized using a BigM coefficient whenever that BigM coefficient is small enough. This control defines the largest BigM for which such a linearized version will be added to the problem in addition to the original constraint. If the BigM is even smaller than INDPRELINBIGM, then the original indicator constraint will additionally be dropped from the problem.
TreeMemorySavingTarget	7,100	When the memory used by the branch-and-bound search tree exceeds the limit specified by the TREEMEMORYLIMIT control, the optimizer will try to save memory by writing lower-rated sections of the tree to the tree file. The target amount of memory to save will be enough to bring memory usage back below the limit, plus enough extra to give the tree room to grow. The TREEMEMORYSAVINGTARGET control specifies the extra proportion of the tree's size to try to save; for example, if the tree memory limit is 1000Mb and TREEMEMORYSAVINGTARGET is 0.1, when the tree size exceeds 1000Mb the optimizer will try to reduce the tree size to 900Mb. Reducing the value of TREEMEMORYSAVINGTARGET will cause less extra nodes of the tree to be written to the tree file, but will result in the memory saving routine being triggered more often (as the tree will have less room in which to grow), which can reduce performance. Increasing the value of TREEMEMORYSAVINGTARGET will cause additional, more highly-rated nodes, of the tree to be written to the tree file, which can cause performance issues if these nodes are required later in the solve.
IndPreLinBigM	7,102	During presolve, indicator constraints will be linearized using a BigM coefficient whenever that BigM coefficient is small enough. This control defines the largest BigM for which the original constraint will be replaced by the linearized version. If the BigM is larger than INDPRELINBIGM but smaller than INDLINBIGM, the linearized row will be added but the original indicator constraint is kept as a numerically stable way to check feasibility.
RelaxTreeMemoryLimit	7,105	When the memory used by the branch and bound search tree exceeds the target specified by the TREEMEMORYLIMIT control, the optimizer will try to reduce this by writing nodes to the tree file. In rare cases, usually where the solve has many millions of very small nodes, the tree structural data (which cannot be written to the tree file) will grow large enough to approach or exceed the tree's memory target. When this happens, optimizer performance can degrade greatly as the solver makes heavy use of the tree file in preference to memory. To prevent this, the solver will automatically relax the tree memory limit when it detects this case; the RELAXTREEMEMORYLIMIT control specifies the proportion of the previous memory limit by which to relax it. Set RELAXTREEMEMORYLIMIT to 0.0 to force the Xpress Optimizer to never relax the tree memory limit in this way.
MIPAbsGapNotifyObj	7,108	Branch and bound: if the gapnotify callback has been set using addCbGapNotify, then this callback will be triggered during the tree search when the best solution value reaches or passes the value you set of the MIPRELGAPNOTIFYOBJ control.
MIPAbsGapNotifyBound	7,109	Branch and bound: if the gapnotify callback has been set using addCbGapNotify, then this callback will be triggered during the tree search when the best bound reaches or passes the value you set of the MIPRELGAPNOTIFYBOUND control.
PresolveMaxGrow	7,110	Limit on how much the number of non-zero coefficients is allowed to grow during presolve, specified as a ratio of the number of non-zero coefficients in the original problem.
HeurSearchTargetSize	7,112
CrossOverRelPivotTol	7,113
CrossOverRelPivotTolSafe	7,114
DetLogFreq	7,116
MaxImpliedBound	7,120	Presolve: When tighter bounds are calculated during MIP preprocessing, only bounds whose absolute value are smaller than MAXIMPLIEDBOUND will be applied to the problem.
FeasTolTarget	7,121	This specifies the target feasibility tolerance for the solution refiner.
OptimalityTolTarget	7,122	This specifies the target optimality tolerance for the solution refiner.
PreComponentsEffort	7,124	Presolve: adjusts the overall effort for the independent component presolver. This control affects working limits for the subproblem solving as well as thresholds when it is called. Increase to put more emphasis on component presolving.
LPLogDelay	7,127	Time interval between two LP log lines.
HeurDiveIterLimit	7,128	Branch and Bound: Simplex iteration limit for reoptimizing during the diving heuristic.
BarKernel	7,130	Newton barrier: Defines how centrality is weighted in the barrier algorithm.
FeasTolPerturb	7,132	This tolerance determines how much a feasible primal basic solution is allowed to be perturbed when performing basis changes. The tolerance FEASTOL is always considered as an upper limit for the perturbations, but in some cases smaller value can be more desirable.
CrossOverFeasWeight	7,133
LUPivotTol	7,139
MIPRestartGapThreshold	7,140	Branch and Bound: Initial gap threshold to delay in-tree restart. The restart is delayed initially if the gap, given as a fraction between 0 and 1, is below this threshold. The optimizer adjusts the threshold every time a restart is delayed. Note that there are other criteria that can delay or prevent a restart.
NodeProbingEffort	7,141	Adjusts the overall level of node probing.
Inputtol	7,143	The tolerance on input values elements. If any value is less than or equal to INPUTTOL in absolute value, it is treated as zero. For the internal zero tolerance see MATRIXTOL.
MIPRestartFactor	7,145	Branch and Bound: Fine tune initial conditions to trigger an in-tree restart. Use a value > 1 to increase the aggressiveness with which the Optimizer restarts. Use a value < 1 to relax the aggressiveness with which the Optimizer restarts. Note that this control does not affect the initial condition on the gap, which must be set separately.
BarObjPerturb	7,146	Defines how the barrier perturbs the objective.
CpiAlpha	7,149	decay term for confined primal integral computation.
GlobalSpatialBranchPropagationEffort	7,152	Limits the effort that is spent on propagation during spatial branching.
GlobalSpatialBranchCuttingEffort	7,153	Limits the effort that is spent on creating cuts during spatial branching.
GlobalBoundingBox	7,154	If a nonlinear problem cannot be solved due to appearing unbounded, it can automatically be regularized by the application of a bounding box on the variables. If this control is set to a negative value, in a second solving attempt all original variables will be bounded by the absolute value of this control. If set to a positive value, there will be a third solving attempt afterwards, if necessary, in which also all auxiliary variables are bounded by this value.
TimeLimit	7,158	The maximum time in seconds that the Optimizer will run before it terminates, including the problem setup time and solution time. For MIP problems, this is the total time taken to solve all nodes.
SolTimeLimit	7,159	The maximum time in seconds that the Optimizer will run a MIP solve before it terminates, given that a solution has been found. As long as no solution has been found, this control will have no effect.
RepairInfeasTimeLimit	7,160	Overall time limit for the repairinfeas tool
BarhgExtrapolate	7,166	Extrapolation parameter for the hybrid gradient algorithm. Although theory suggests that a value of 1 is best, slightly smaller values perform better in general.
WorkLimit	7,167	The maximum work (measured in work units) that the Optimizer will run before it terminates. WORK is accumulated during the search and ever increasing. In contrast to TIME, WORK is independent of the hardware and platform on which the search is conducted. The WORKLIMIT serves as a deterministic stopping criterion. When it is reached, it leaves the optimizer in a reproducible state.
CallbackCheckTimeWorkDelay	7,169	Minimum delay in work units between two consecutive executions of the CHECKTIME callback in the same solution process
PreRootWorkLimit	7,172	Set an explicit work limit in work units for the Pre-root parallel heuristic phase. Any positive value also enables this phase and runs it until the PREROOTWORKLIMIT units of work are hit.
PreRootEffort	7,173	Dial for the work spent during the Pre-root parallel heuristic phase. A positive value sets a suitable work limit that is dependent on problem-characteristics. Changing the value up/or down dials the work spent in this phase up or down. This control also enables/disables Pre-root parallel heuristics.
ExtraRows	8,004	The initial number of extra rows to allow for in the matrix, including cuts. If rows are to be added to the matrix, then, for maximum efficiency, space should be reserved for the rows before the matrix is input by setting the EXTRAROWS control. If this is not done, resizing will occur automatically, but more space may be allocated than the user actually requires.
ExtraCols	8,005	The initial number of extra columns to allow for in the matrix. If columns are to be added to the matrix, then, for maximum efficiency, space should be reserved for the columns before the matrix is input by setting the EXTRACOLS control. If this is not done, resizing will occur automatically, but more space may be allocated than the user actually requires.
ExtraElems	8,006	The initial number of extra matrix elements to allow for in the matrix, including coefficients for cuts. If rows or columns are to be added to the matrix, then, for maximum efficiency, space should be reserved for the extra matrix elements before the matrix is input by setting the EXTRAELEMS control. If this is not done, resizing will occur automatically, but more space may be allocated than the user actually requires.
LPIterLimit	8,007	The maximum number of iterations that will be performed by primal simplex or dual simplex before the optimization process terminates. For MIP problems, this is the maximum total number of iterations over all nodes explored by the Branch and Bound method.
LPLog	8,009	Simplex: The frequency at which the simplex log is printed.
Scaling	8,010	This bit-vector control (see Section ) determines how the Optimizer will rescale a model internally before optimization. If set to 0, no scaling will take place.
Presolve	8,011	This control determines whether presolving should be performed prior to starting the main algorithm. Presolve attempts to simplify the problem by detecting and removing redundant constraints, tightening variable bounds, etc. In some cases, infeasibility may even be determined at this stage, or the optimal solution found.
Crash	8,012	Simplex: This determines the type of crash used when the algorithm begins. During the crash procedure, an initial basis is determined which is as close to feasibility and triangularity as possible. A good choice at this stage will significantly reduce the number of iterations required to find an optimal solution. The possible values increase proportionally to their time-consumption.
PricingAlg	8,013	Simplex: This determines the primal simplex pricing method. It is used to select which variable enters the basis on each iteration. In general Devex pricing requires more time on each iteration, but may reduce the total number of iterations, whereas partial pricing saves time on each iteration, but may result in more iterations.
InvertFreq	8,014	Simplex: The frequency with which the basis will be inverted. The basis is maintained in a factorized form and on most simplex iterations it is incrementally updated to reflect the step just taken. This is considerably faster than computing the full inverted matrix at each iteration, although after a number of iterations the basis becomes less well-conditioned and it becomes necessary to compute the full inverted matrix. The value of INVERTFREQ specifies the maximum number of iterations between full inversions.
InvertMin	8,015	Simplex: The minimum number of iterations between full inversions of the basis matrix. See the description of INVERTFREQ for details.
MaxNode	8,018	Branch and Bound: The maximum number of nodes that will be explored.
MaxTime	8,020	The maximum time in seconds that the Optimizer will run before it terminates, including the problem setup time and solution time. For MIP problems, this is the total time taken to solve all nodes. Obsolete
MaxMIPSol	8,021	Branch and Bound: This specifies a limit on the number of integer solutions to be found by the Optimizer. It is possible that during optimization the Optimizer will find the same objective solution from different nodes. However, MAXMIPSOL refers to the total number of integer solutions found, and not necessarily the number of distinct solutions.
SiftPasses	8,022	Determines how quickly we allow to grow the worker problems during the sifting algorithm. Using larger values can increase the number of columns added to the worker problem which often results in increased solve times for the worker problems but the number of necessary sifting iterations may be reduced.
DefaultAlg	8,023	This selects the algorithm that will be used to solve LPs, standalone or during MIP optimization.
VarSelection	8,025	Branch and Bound: This determines the formula used to calculate the estimate of each integer variable, and thus which integer variable is selected to be branched on at a given node. The variable selected to be branched on is the one with the maximum estimate.
NodeSelection	8,026	Branch and Bound: This determines which nodes will be considered for solution once the current node has been solved.
BackTrack	8,027	Branch and Bound: Specifies how to select the next node to work on when a full backtrack is performed.
MIPLog	8,028	MIP log print control.
KeepNRows	8,030	How nonbinding rows should be handled by the MPS reader.
MPSEcho	8,032	Determines whether comments in MPS matrix files are to be printed out during matrix input.
MaxPageLines	8,034	Number of lines between page breaks in printable output.
OutputLog	8,035	This controls the level of output produced by the Optimizer during optimization. In the Console Optimizer, OUTPUTLOG controls which messages are sent to the screen (stdout). When using the Optimizer library, no output is sent to the screen. If the user wishes output to be displayed, they must define a callback function and print messages to the screen themselves. In this case, OUTPUTLOG controls which messages are sent to the user output callback.
BarSolution	8,038	This determines whether the barrier has to decide which is the best solution found or return the solution computed by the last barrier iteration.
CacheSize	8,043	Newton Barrier: L2 or L3 (see notes) cache size in kB (kilobytes) of the CPU. On Intel (or compatible) platforms a value of -1 may be used to determine the cache size automatically. If the CPU model is new then the cache size may not be correctly detected by an older release of the software. Obsolete
CrossOver	8,044	Newton barrier and hybrid gradient: This control determines whether the barrier method will cross over to the simplex method when at optimal solution has been found, to provide an end basis (see getBasis, writeBasis) and advanced sensitivity analysis information (see objsa, rHSsa, bndsa).
BarIterLimit	8,045	Newton barrier: The maximum number of iterations. While the simplex method usually performs a number of iterations which is proportional to the number of constraints (rows) in a problem, the barrier method standardly finds the optimal solution to a given accuracy after a number of iterations which is independent of the problem size. The penalty is rather that the time for each iteration increases with the size of the problem. BARITERLIMIT specifies the maximum number of iterations which will be carried out by the barrier.
CholeskyAlg	8,046	Newton barrier: type of Cholesky factorization used; bit-vector-control (see Section ).
BarOutput	8,047	Newton barrier and hybrid gradient: This specifies the level of solution output provided. Output is provided either after each iteration of the algorithm, or else can be turned off completely by this parameter.
ExtraMIPEnts	8,051	The initial number of extra MIP entities to allow for.
Refactor	8,052	Indicates whether the optimization should restart using the current representation of the factorization in memory.
BarThreads	8,053	If set to a positive integer it determines the number of threads implemented to run the Newton-barrier and hybrid gradient algorithms. If the value is set to the default value (-1), the THREADS control will determine the number of threads used.
KeepBasis	8,054	Simplex: This determines whether the basis should be kept when reoptimizing a problem. The choice is between using a crash basis created at the beginning of simplex or using a basis from a previous solve (if such exists). By default, this control gets (re)set automatically in various situations. By default, it will be automatically set to 1 after a solve that produced a valid basis. This will automatically warmstart a subsequent solve. Explicitly loading a starting basis will also set this control to 1. If the control is explicitly set to 0, any existing basis will be ignored for a new solve, and the Optimizer will start from an ad-hoc crash basis.
CrossoverOps	8,060	Newton barrier and hybrid gradient: a bit-vector (see Section ) for adjusting the behavior of the crossover procedure.
Version	8,061	The Optimizer version number, e.g. 1301 meaning release 13.01.
CrossoverThreads	8,065	Determines the maximum number of threads that parallel crossover is allowed to use. If CROSSOVERTHREADS is set to the default value (-1), the BARTHREADS control will determine the number of threads used.
BigmMethod	8,068	Simplex: This specifies whether to use the "Big M" method, or the standard phase I (achieving feasibility) and phase II (achieving optimality). In the "Big M" method, the objective coefficients of the variables are considered during the feasibility phase, possibly leading to an initial feasible basis which is closer to optimal. The side-effects involve possible round-off errors due to the presence of the "Big M" factor in the problem.
MPSNameLength	8,071
ElimFillIn	8,073	Amount of fill-in allowed when performing an elimination in presolve .
PresolveOps	8,077	This bit-vector control (see Section ) specifies the operations which are performed during the presolve.
MIPPresolve	8,078	Branch and Bound: Type of integer processing to be performed. If set to 0, no processing will be performed. This is a bit-vector control (see Section ).
MIPThreads	8,079	If set to a positive integer it determines the number of threads implemented to run the parallel MIP code. If MIPTHREADS is set to the default value (-1), the THREADS control will determine the number of threads used.
BarOrder	8,080	Newton barrier: This controls the Cholesky factorization in the Newton-Barrier.
BreadthFirst	8,082	The number of nodes to include in the best-first search before switching to the local first search (NODESELECTION=4).
AutoPerturb	8,084	Simplex: This indicates whether automatic perturbation is performed. If this is set to 1, the problem will be perturbed whenever the simplex method encounters an excessive number of degenerate pivot steps, thus preventing the Optimizer being hindered by degeneracies.
DenseColLimit	8,086	Newton barrier: Columns with more than DENSECOLLIMIT elements are considered to be dense. Such columns will be handled specially in the Cholesky factorization of this matrix.
CallbackFromMasterThread	8,090	Branch and Bound: specifies whether the MIP callbacks should only be called on the master thread.
MaxMCoeffBufferElems	8,091	The maximum number of matrix coefficients to buffer before flushing into the internal representation of the problem. Buffering coefficients can offer a significant performance gain when you are building a matrix using chgCoef or chgMCoef, but can lead to a significant memory overhead for large matrices, which this control allows you to influence.
RefineOps	8,093	This specifies when the solution refiner should be executed to reduce solution infeasibilities. The refiner will attempt to satisfy the target tolerances for all original linear constraints before presolve or scaling has been applied.
LpRefineIterLimit	8,094	This specifies the simplex iteration limit the solution refiner can spend in attempting to increase the accuracy of an LP solution.
MipRefineIterLimit	8,095	This defines an effort limit expressed as simplex iterations for the MIP solution refiner. The limit is per reoptimizations in the MIP refiner.
DualizeOps	8,097	Bit-vector control (see Section ) for adjusting the behavior when a problem is dualized.
CrossoverIterLimit	8,104	Newton barrier and hybrid gradient: The maximum number of iterations that will be performed in the crossover procedure before the optimization process terminates.
PreBasisRed	8,106	Determines if a lattice basis reduction algorithm should be attempted as part of presolve
PreSort	8,107	This bit-vector control (see Section ) specifies whether to sort rows, columns and MIP entities by their names when starting the presolve. With the default value 0, no sorting will take place.
PrePermute	8,108	This bit-vector control (see Section ) specifies whether to randomly permute rows, columns and MIP entities when starting the presolve. With the default value 0, no permutation will take place.
PrePermuteSeed	8,109	This control sets the seed for the pseudo-random number generator for permuting the problem when starting the presolve. This control only has effects when PREPERMUTE is enabled.
MaxMemorySoft	8,112	When RESOURCESTRATEGY is enabled, this control sets the maximum amount of memory in megabytes the optimizer targets to allocate. This may change the solving path, but will not cause the solve to terminate early. To set a hard version of the same, please set MAXMEMORYHARD.
CutFreq	8,116	Branch and Bound: This specifies the frequency at which cuts are generated in the tree search. If the depth of the node modulo CUTFREQ is zero, then cuts will be generated.
SymSelect	8,117	Adjusts the overall amount of effort for symmetry detection.
Symmetry	8,118	Adjusts the overall amount of effort for symmetry detection.
MaxMemoryHard	8,119	This control sets the maximum amount of memory in megabytes the optimizer should allocate. If this limit is exceeded, the solve will terminate. This control is designed to make the optimizer stop in a controlled manner, so that the problem object is valid once termination occurs. The solve state will be set to incomplete. This is different to an out of memory condition in which case the optimizer returns an error. The optimizer may still allocate memory once the limit is exceeded to be able to finsish the operations and stop in a controlled manner. When RESOURCESTRATEGY is enabled, the control also has the same effect as MAXMEMORYSOFT and will cause the optimizer to try preserving memory when possible.
MIQCPAlg	8,125	This control determines which algorithm is to be used to solve mixed integer quadratic constrained and mixed integer second order cone problems.
QCCuts	8,126	Branch and Bound: Limit on the number of rounds of outer approximation cuts generated for the root node, when solving a mixed integer quadratic constrained or mixed integer second order conic problem with outer approximation.
QCRootAlg	8,127	This control determines which algorithm is to be used to solve the root of a mixed integer quadratic constrained or mixed integer second order cone problem, when outer approximation is used.
PreConvertSeparable	8,128	Presolve: reformulate problems with a non-diagonal quadratic objective and/or constraints as diagonal quadratic or second-order conic constraints.
AlgAfterNetwork	8,129	The algorithm to be used for the clean up step after the network simplex solver.
Trace	8,130	Display the infeasibility diagnosis during presolve. If non-zero, an explanation of the logical deductions made by presolve to deduce infeasibility or unboundedness will be displayed on screen or sent to the message callback function.
MaxIIS	8,131	This function controls the number of Irreducible Infeasible Sets to be found using the iISAll (IIS-a).
CPUTime	8,133	How time should be measured when timings are reported in the log and when checking against time limits
CoverCuts	8,134	Branch and Bound: The number of rounds of lifted cover inequalities at the root node. A lifted cover inequality is an additional constraint that can be particularly effective at reducing the size of the feasible region without removing potential integral solutions. The process of generating these can be carried out a number of times, further reducing the feasible region, albeit incurring a time penalty. There is usually a good payoff from generating these at the root node, since these inequalities then apply to every subsequent node in the tree search.
GomCuts	8,135	Branch and Bound: The number of rounds of Gomory or lift-and-project cuts at the root node.
LpFolding	8,136	Simplex and barrier: whether to fold an LP problem before solving it.
MPSFormat	8,137	Specifies the format of MPS files.
CutStrategy	8,138	Branch and Bound: This specifies the cut strategy. A more aggressive cut strategy, generating a greater number of cuts, will result in fewer nodes to be explored, but with an associated time cost in generating the cuts. The fewer cuts generated, the less time taken, but the greater subsequent number of nodes to be explored.
CutDepth	8,139	Branch and Bound: Sets the maximum depth in the tree search at which cuts will be generated. Generating cuts can take a lot of time, and is often less important at deeper levels of the tree since tighter bounds on the variables have already reduced the feasible region. A value of 0 signifies that no cuts will be generated.
TreeCoverCuts	8,140	Branch and Bound: The number of rounds of lifted cover inequalities generated at nodes other than the root node in the tree. Compare with the description for COVERCUTS. A value of -1 indicates the number of rounds is determined automatically.
TreeGomCuts	8,141	Branch and Bound: The number of rounds of Gomory cuts generated at nodes other than the first node in the tree. Compare with the description for GOMCUTS. A value of -1 indicates the number of rounds is determined automatically.
CutSelect	8,142	A bit-vector (see Section ) providing detailed control of the cuts created for the root node of a MIP solve. Use TREECUTSELECT to control cuts during the tree search.
TreeCutSelect	8,143	A bit-vector (see Section ) providing detailed control of the cuts created during the tree search of a MIP solve. Use CUTSELECT to control cuts on the root node.
Dualize	8,144	For a linear problem or the initial linear relaxation of a MIP, determines whether to form and solve the dual problem.
DualGradient	8,145	Simplex: This specifies the dual simplex pricing method.
SBIterLimit	8,146	Number of dual iterations to perform the strong branching for each entity.
SBBest	8,147	Number of infeasible MIP entities to initialize pseudo costs for on each node.
MaxCutTime	8,149	The maximum amount of time allowed for generation of cutting planes and reoptimization. The limit is checked during generation and no further cuts are added once this limit has been exceeded.
BarIndefLimit	8,153	Newton Barrier. This limits the number of consecutive indefinite barrier iterations that will be performed. The optimizer will try to minimize (resp. maximize) a QP problem even if the Q matrix is not positive (resp. negative) semi-definite. However, the optimizer may detect that the Q matrix is indefinite and this can result in the optimizer not converging. This control specifies how many indefinite iterations may occur before the optimizer stops and reports that the problem is indefinite. It is usual to specify a value greater than one, and only stop after a series of indefinite matrices, as the problem may be found to be indefinite incorrectly on a few iterations for numerical reasons.
HeurFreq	8,155	Branch and Bound: This specifies the frequency at which heuristics are used in the tree search. Heuristics will only be used at a node if the depth of the node is a multiple of HEURFREQ.
HeurDepth	8,156	Branch and Bound: Sets the maximum depth in the tree search at which heuristics will be used to find MIP solutions. It may be worth stopping the heuristic search for solutions after a certain depth in the tree search. A value of 0 signifies that heuristics will not be used. This control no longer has any effect and will be removed from future releases.
HeurMaxSol	8,157	Branch and Bound: This specifies the maximum number of heuristic solutions that will be found in the tree search. This control no longer has any effect and will be removed from future releases.
HeurNodes	8,158	Branch and Bound: This specifies the maximum number of nodes at which heuristics are used in the tree search. This control no longer has any effect and will be removed from future releases.
LNPBest	8,160	Number of infeasible MIP entities to create lift-and-project cuts for during each round of Gomory cuts at the root node (see GOMCUTS).
LNPIterLimit	8,161	Number of iterations to perform in improving each lift-and-project cut.
BranchChoice	8,162	Once a MIP entity has been selected for branching, this control determines which of the branches is solved first.
BarRegularize	8,163	This bit-vector control (see Section ) determines how the barrier algorithm applies regularization on the KKT system.
SBSelect	8,164	The size of the candidate list of MIP entities for strong branching.
IISLog	8,165	Selects how much information should be printed during the IIS procedure. Please refer to Appendix for a more detailed description of the IIS logging format.
LocalChoice	8,170	Controls when to perform a local backtrack between the two child nodes during a dive in the branch and bound tree.
LocalBacktrack	8,171
DualStrategy	8,174	This bit-vector control (see Section ) specifies the dual simplex strategy.
L1Cache	8,175	Newton barrier: L1 cache size in kB (kilo bytes) of the CPU. On Intel (or compatible) platforms a value of -1 may be used to determine the cache size automatically. Obsolete
HeurDiveStrategy	8,177	Branch and Bound: Chooses the strategy for the diving heuristic.
HeurSelect	8,178
BarStart	8,180	Controls the computation of the starting point and warm-starting for the Newton barrier and the hybrid gradient algorithms.
PresolvePasses	8,183	Number of reduction rounds to be performed in presolve
BarNumStability	8,186	Obsolete
BarOrderThreads	8,187	If set to a positive integer it determines the number of concurrent threads for the sparse matrix ordering algorithm in the Newton-barrier method.
ExtraSets	8,190	The initial number of extra sets to allow for in the matrix. If sets are to be added to the matrix, then, for maximum efficiency, space should be reserved for the sets before the matrix is input by setting the EXTRASETS control. If this is not done, resizing will occur automatically, but more space may be allocated than the user actually requires.
ExtraSetElems	8,191	The initial number of extra elements in sets to allow for in the matrix. If sets are to be added to the matrix, then, for maximum efficiency, space should be reserved for the set elements before the matrix is input by setting the EXTRASETELEMS control. If this is not done, resizing will occur automatically, but more space may be allocated than the user actually requires.
FeasibilityPump	8,193	Branch and Bound: Decides if the Feasibility Pump heuristic should be run at the root node.
PreCoefElim	8,194	Presolve: Specifies whether the optimizer should attempt to recombine constraints in order to reduce the number of non zero coefficients when presolving a mixed integer problem.
PreDomCol	8,195	Presolve: Determines the level of dominated column removal reductions to perform when presolving a mixed integer problem. Only binary columns will be checked.
HeurSearchFreq	8,196	Branch and Bound: This specifies how often the local search heuristic should be run in the tree.
HeurDiveSpeedUp	8,197	Branch and Bound: Changes the emphasis of the diving heuristic from solution quality to diving speed.
SBEstimate	8,198	Branch and Bound: How to calculate pseudo costs from the local node when selecting an infeasible MIP entity to branch on. These pseudo costs are used in combination with local strong branching and history costs to select the branch candidate.
BarCores	8,202	If set to a positive integer it determines the number of physical CPU cores assumed to be present in the system by the barrier and hybrid gradient algorithms. If the value is set to the default value (-1), Xpress will automatically detect the number of cores.
MaxChecksOnMaxTime	8,203	This control is intended for use where optimization runs that are terminated using the TIMELIMIT (or the deprecated MAXTIME) control are required to be reproduced exactly. This control is necessary because of the inherent difficulty in terminating algorithmic software in a consistent way using temporal criteria. The control value relates to the number of times the optimizer checks the TIMELIMIT criterion up to and including the check when the termination was activated. To use the control the user first must obtain the value of the CHECKSONMAXTIME attribute after the run returns. This attribute value is the number of times the optimizer checked the TIMELIMIT criterion during the last call to the optimization routine mipOptimize. Note that this attribute value will be negative if the optimizer terminated on the TIMELIMIT criterion. To ensure that a reproduction of a run terminates in the same way the user should first ensure that TIMELIMIT is set to its default value or to a large value so the run does not terminate again on TIMELIMIT and then simply set the control MAXCHECKSONMAXTIME to the absolute value of the CHECKSONMAXTIME value.
MaxChecksOnMaxCutTime	8,204	This control is intended for use where optimization runs that are terminated using the MAXCUTTIME control are required to be reproduced exactly. This control is necessary because of the inherent difficulty in terminating algorithmic software in a consistent way using temporal criteria. The control value relates to the number of times the optimizer checks the MAXCUTTIME criterion up to and including the check when the termination of cutting was activated. To use the control the user first must obtain the value of the CHECKSONMAXCUTTIME attribute after the run returns. This attribute value is the number of times the optimizer checked the MAXCUTTIME criterion during the last call to the optimization routine mipOptimize. Note that this attribute value will be negative if the optimizer terminated cutting on the MAXCUTTIME criterion. To ensure accurate reproduction of a run the user should first ensure that MAXCUTTIME is set to its default value or to a large value so the run does not terminate again on MAXCUTTIME and then simply set the control MAXCHECKSONMAXCUTTIME to the absolute value of the CHECKSONMAXCUTTIME value.
HistoryCosts	8,206	Branch and Bound: How to update the pseudo cost for a MIP entity when a strong branch or a regular branch is applied.
AlgAfterCrossOver	8,208	The algorithm to be used for the final clean up step after the crossover.
MutexCallBacks	8,210	Branch and Bound: This determines whether the callback routines are mutexed from within the optimizer.
BarCrash	8,211	Newton barrier and hybrid gradient: This determines the type of crash used for the crossover. During the crash procedure, an initial basis is determined which attempts to speed up the crossover. A good choice at this stage will significantly reduce the number of iterations required to crossover to an optimal solution. The possible values increase proportionally to their time-consumption.
HeurDiveSoftRounding	8,215	Branch and Bound: Enables a more cautious strategy for the diving heuristic, where it tries to push binaries and integer variables to their bounds using the objective, instead of directly fixing them. This can be useful when the default diving heuristics fail to find any feasible solutions.
HeurSearchRootSelect	8,216	A bit-vector control (see Section ) for selecting which local search heuristics to apply on the root node of a MIP solve. Use HEURSEARCHTREESELECT to control local search heuristics during the tree search.
HeurSearchTreeSelect	8,217	A bit-vector control (see Section ) for selecting which local search heuristics to apply during the tree search of a MIP solve. Use HEURSEARCHROOTSELECT to control local search heuristics on the root node.
MPS18Compatible	8,223	Provides compatibility of MPS file output for older MPS readers.
RootPresolve	8,224	Determines if presolving should be performed on the problem after the tree search has finished with root cutting and heuristics.
CrossOverDRP	8,227
ForceOutput	8,229	Certain names in the problem object may be incompatible with different file formats (such as names containing spaces for LP files). If the optimizer might be unable to read back a problem because of non-standard names, it will first attempt to write it out using an extended naming convention. If the names would not be possible to extend so that they would be reproducible and recognizable, it will give an error message and won't create the file. If the optimizer might be unable to read back a problem because of non-standard names, it will give an error message and won't create the file. This option may be used to force output anyway.
PrimalOps	8,231	Primal simplex: allows fine tuning the variable selection in the primal simplex solver.
Deterministic	8,232	Selects whether to use a deterministic or opportunistic mode when solving a problem using multiple threads.
PreProbing	8,238	Presolve: Amount of probing to perform on binary variables during presolve. This is done by fixing a binary to each of its values in turn and analyzing the implications.
TreeMemoryLimit	8,242	A soft limit, in megabytes, for the amount of memory to use in storing the branch and bound search tree. This doesn't include memory used for presolve, heuristics, solving the LP relaxation, etc. When set to 0 (the default), the optimizer will calculate a limit automatically based on the amount of free physical memory detected in the machine. When the memory used by the branch and bound tree exceeds this limit, the optimizer will try to reduce the memory usage by writing lower-rated sections of the tree to a file called the "tree file". Though the solve can continue if it cannot bring the tree memory usage below the specified limit, performance will be inhibited and a message will be printed to the log.
TreeCompression	8,243	When writing nodes to the gloal file, the optimizer can try to use data-compression techniques to reduce the size of the tree file on disk. The TREECOMPRESSION control determines the strength of the data-compression algorithm used; higher values give superior data-compression at the affect of decreasing performance, while lower values compress quicker but not as effectively. Where TREECOMPRESSION is set to 0, no data compression will be used on the tree file.
TreeDiagnostics	8,244	A bit-vector (see Section ) providing control over how various tree-management-related messages get printed in the tree log file during the branch-and-bound search.
MaxTreeFileSize	8,245	The maximum size, in megabytes, to which the tree file may grow, or 0 for no limit. When the tree file reaches this limit, a second tree file will be created. Useful if you are using a filesystem that puts a maximum limit on the size of a file.
PreCliqueStrategy	8,247	Determines how much effort to spend on clique covers in presolve.
RepairInfeasMaxTime	8,250	Overall time limit for the repairinfeas tool Obsolete
IfCheckConvexity	8,251	Determines if the convexity of the problem is checked before optimization. Applies to quadratic, mixed integer quadratic and quadratically constrained problems. Checking convexity takes some time, thus for problems that are known to be convex it might be reasonable to switch the checking off.
PrimalUnshift	8,252	Determines whether primal is allowed to call dual to unshift.
RepairIndefiniteQ	8,254	Controls if the optimizer should make indefinite quadratic matrices positive definite when it is possible.
MipRampup	8,255	Controls the strategy used by the parallel MIP solver during the ramp-up phase of a branch-and-bound tree search.
MaxLocalBacktrack	8,257	Branch-and-Bound: How far back up the current dive path the optimizer is allowed to look for a local backtrack candidate node.
UserSolHeuristic	8,258	Determines how much effort to put into running a local search heuristic to find a feasible integer solution from a partial or infeasible user solution.
PreConvertObjToCons	8,260	Presolve: convert a linear or quadratic objective function into an objective transfer constraint
ForceParallelDual	8,265	Dual simplex: specifies whether the dual simplex solver should always use the parallel simplex algorithm. By default, when using a single thread, the dual simplex solver will execute a dedicated sequential simplex algorithm.
BacktrackTie	8,266	Branch and Bound: Specifies how to break ties when selecting the next node to work on when a full backtrack is performed. The options are the same as for the BACKTRACK control.
BranchDisj	8,267	Branch and Bound: Determines whether the optimizer should attempt to branch on general split disjunctions during the branch and bound search.
MipFracReduce	8,270	Branch and Bound: Specifies how often the optimizer should run a heuristic to reduce the number of fractional integer variables in the node LP solutions.
ConcurrentThreads	8,274	Determines the number of threads used by the concurrent solver.
MaxScaleFactor	8,275	This determines the maximum scaling factor that can be applied during scaling. The maximum is provided as an exponent of a power of 2.
HeurThreads	8,276	Branch and Bound: The number of threads to dedicate to running heuristics during the root solve.
Threads	8,278	The default number of threads used during optimization.
HeurBeforeLP	8,280	Branch and Bound: Determines whether primal heuristics should be run before the initial LP relaxation has been solved.
PreDomRow	8,281	Presolve: Determines the level of dominated row removal reductions to perform when presolving a problem.
BranchStructural	8,282	Branch and Bound: Determines whether the optimizer should search for special structure in the problem to branch on during the branch and bound search.
QuadraticUnshift	8,284	Determines whether an extra solution purification step is called after a solution found by the quadratic simplex (either primal or dual).
BarPresolveOps	8,286	Newton barrier: This bit-vector (see Section ) controls the Newton-Barrier specific presolve operations.
QSimplexOps	8,288	Controls the behavior of the quadratic simplex solvers via a bit-vector (see Section ).
MipRestart	8,290	Branch and Bound: controls strategy for in-tree restarts.
ConflictCuts	8,292	Branch and Bound: Specifies how cautious or aggressive the optimizer should be when searching for and applying conflict cuts. Conflict cuts are in-tree cuts derived from nodes found to be infeasible or cut off, which can be used to cut off other branches of the search tree.
PreProtectDual	8,293	Presolve: specifies whether the presolver should protect a given dual solution by maintaining the same level of dual feasibility. Enabling this control often results in a worse presolved model. This control only expected to be optionally enabled before calling crossoverLpSol.
CoresPerCPU	8,296	Used to override the detected value of the number of cores on a CPU. The cache size (either detected or specified via the CACHESIZE control) used in Barrier methods will be divided by this amount, and this scaled-down value will be the amount of cache allocated to each Barrier thread
ResourceStrategy	8,297	Controls whether the optimizer is allowed to make nondeterministic decisions if memory is running low in an effort to preserve memory and finish the solve. Available memory (or container limits) are automatically detected but can also be changed by MAXMEMORYSOFT and MAXMEMORYHARD
Clamping	8,301	This bit-vector control (see Section ) allows for the adjustment of returned solution values such that they are always within bounds.
SleepOnThreadWait	8,302	In previous versions this was used to determine if the threads should be put into a wait state when waiting for work. Obsolete
PreDupRow	8,307	Presolve: Determines the type of duplicate rows to look for and eliminate when presolving a problem.
CPUPlatform	8,312	Newton Barrier: Selects the AMD, Intel x86 or ARM vectorization instruction set that Barrier should run optimized code for. On AMD / Intel x86 platforms the SSE2, AVX and AVX2 instruction sets are supported while on ARM platforms the NEON architecture extension can be activated.
BarAlg	8,315	This control determines which barrier algorithm is used to solve the problem. Notably, this is also the control to enable the primal-dual hybrid gradient algorithm.
Sifting	8,319	Determines whether to enable sifting algorithm with the dual simplex method.
BarKeepLastSol	8,323
LPLogStyle	8,326	Simplex: The style of the simplex log.
RandomSeed	8,328	Sets the initial seed to use for the pseudo-random number generator in the Optimizer. The sequence of random numbers is always reset using the seed when starting a new optimization run.
TreeQCCuts	8,331	Branch and Bound: Limit on the number of rounds of outer approximation cuts generated for nodes other than the root node, when solving a mixed integer quadratic constrained or mixed integer second order conic problem with outer approximation.
PreLinDep	8,333	Presolve: Determines whether to check for and remove linearly dependent equality constraints when presolving a problem.
DualThreads	8,334	Determines the maximum number of threads that dual simplex is allowed to use. If DUALTHREADS is set to the default value (-1), the THREADS control will determine the number of threads used.
PreObjCutDetect	8,336	Presolve: Determines whether to check for constraints that are parallel or near parallel to a linear objective function, and which can safely be removed. This reduction applies to MIPs only.
PreBndRedQuad	8,337	Determines if convex quadratic constraints should be used for inferring bound reductions on variables when solving a MIP.
PreBndRedCone	8,338	Determines if second order cone constraints should be used for inferring bound reductions on variables when solving a MIP.
PreComponents	8,339	Presolve: determines whether small independent components should be detected and solved as individual subproblems during root node processing.
MaxMipTasks	8,347	Branch-and-Bound: The maximum number of tasks to run in parallel during a MIP solve.
MipTerminationMethod	8,348	Branch and Bound: How a MIP solve should be stopped on early termination when there are still active tasks in the system. This can happen when, for example, a time or node limit is reached.
PreConeDecomp	8,349	Presolve: decompose regular and rotated cones with more than two elements and apply Outer Approximation on the resulting components.
HeurForceSpecialObj	8,350	Branch and Bound: This specifies whether local search heuristics without objective or with an auxiliary objective should always be used, despite the automatic selection of the Optimiezr. Deactivated by default.
HeurSearchRootCutFreq	8,351	How frequently to run the local search heuristic during root cutting. This is given as how many cut rounds to perform between runs of the heuristic. Set to zero to avoid applying the heuristic during root cutting. Branch and Bound: This specifies how often the local search heuristic should be run in the tree.
PreElimQuad	8,353	Presolve: Allows for elimination of quadratic variables via doubleton rows.
PreImplications	8,356	Presolve: Determines whether to use implication structures to remove redundant rows. If implication sequences are detected, they might also be used in probing.
TunerMode	8,359	Tuner: Whether to always enable the tuner or disable it.
TunerMethod	8,360	Tuner: Selects a factory tuner method. A tuner method consists of a list of controls with different settings that the tuner will evaluate and try to combine.
TunerTarget	8,362	Tuner: Defines the tuner target -- what should be evaluated when comparing two runs with different control settings.
TunerThreads	8,363	Tuner: the number of threads used by the tuner.
TunerMaxTime	8,364	Tuner: The maximum time in seconds that the tuner will run before it terminates.
TunerHistory	8,365	Tuner: Whether to reuse and append to previous tuner results of the same problem.
TunerPermute	8,366	Tuner: Defines the number of permutations to solve for each control setting.
TunerVerbose	8,370	Tuner: whether the tuner should prints detailed information for each run.
TunerOutput	8,372	Tuner: Whether to output tuner results and logs to the file system.
PreAnalyticcenter	8,374	Determines if analytic centers should be computed and used for variable fixing and the generation of alternative reduced costs (-1: Auto 0: Off, 1: Fixing, 2: Redcost, 3: Both)
NetCuts	8,382	Obsolete
LPFlags	8,385	A bit-vector control (see Section ) which defines the algorithm for solving an LP problem or the initial LP relaxation of a MIP problem.
MIPKappaFreq	8,386	Branch and Bound: Specifies how frequently the basis condition number (also known as kappa) should be calculated during the branch-and-bound search.
ObjScaleFactor	8,387	Custom objective scaling factor, expressed as a power of 2. When set, it overwrites the automatic objective scaling factor. A value of 0 means no objective scaling. This control is applied for the full solve, and is independent of any extra scaling that may occur specifically for the barrier or simplex solvers. As it is a power of 2, to scale by 16, set the value of the control to 4.
TreeFileLogInterval	8,389	This control sets the interval between progress messages output while writing tree data to the tree file, in seconds. The solve is slowed greatly while data is being written to the tree file and this output allows the user to see how much progress is being made.
IgnoreContainerCpuLimit	8,390
IgnoreContainerMemoryLimit	8,391
MIPDualReductions	8,392	Branch and Bound: Limits operations that can reduce the MIP solution space.
GenconsDualReductions	8,395	This parameter specifies whether dual reductions should be applied to reduce the number of columns and rows added when transforming general constraints to MIP structs.
PwlDualReductions	8,396	This parameter specifies whether dual reductions should be applied to reduce the number of columns, rows and SOS-constraints added when transforming piecewise linear objectives and constraints to MIP structs.
BarFailIterLimit	8,398	Newton barrier: The maximum number of consecutive iterations that fail to improve the solution in the barrier algorithm.
AutoScaling	8,406	Whether the Optimizer should automatically select between different scaling algorithms. If the SCALING control is set, no automatic scaling will be applied.
GenconsAbsTransformation	8,408	This control specifies the reformulation method for absolute value general constraints at the beginning of the search.
ComputeJobPriority	8,409	Selects the priority that will be used for remote optimization jobs.
PreFolding	8,410	Presolve: Determines if a folding procedure should be used to aggregate continuous columns in an equitable partition.
Compute	8,411	Controls whether the next solve is performed directly or on an Insight Compute Interface.
NetStallLimit	8,412	Limit the number of degenerate pivots of the network simplex algorithm, before switching to either primal or dual simplex, depending on ALGAFTERNETWORK.
SerializePreIntSol	8,413	Setting SERIALIZEPREINTSOL to 1 will ensure that the preintsol callback is always fired in a deterministic order during a parallel MIP solve. This applies only when the control DETERMINISTIC is set to 1.
NumericalEmphasis	8,416	How much emphasis to place on numerical stability instead of solve speed.
PwlNonConvexTransformation	8,420	This control specifies the reformulation method for piecewise linear constraints at the beginning of the search. Note that the chosen formulation will only be used if MIP entities are necessary but not if presolve detected that a convex reformulation is possible. Furthermore, the binary formulation will only be applied to piecewise linear constraints with bounded input variable, otherwise the SOS2-formulation will be used.
MipComponents	8,421	Determines whether disconnected components in a MIP should be solved as separate MIPs. There can be significant performence benefits from solving disconnected components individual instead of being part of the main branch-and-bound search.
MipConcurrentNodes	8,422	Sets the node limit for when a winning solve is selected when concurrent MIP solves are enabled. When multiple MIP solves are started, they each run up to the MIPCONCURRENTNODES node limit and only one winning solve is selected for contuinuing the search with.
MipConcurrentSolves	8,423	Selects the number of concurrent solves to start for a MIP. Each solve will use a unique random seed for its random number generator, but will otherwise apply the same user controls. The first concurrent solve to complete will have solved the MIP and all the concurrent solves will be terminated at this point. Using concurrent solves can be advantageous when a MIP displays a high level of performance variability.
OutputControls	8,424	This control toggles the printing of all control settings at the beginning of the search. This includes the printing of controls that have been explicitly assigned to their default value. All unset controls are omitted as they keep their default value.
SiftSwitch	8,425	Determines which algorithm to use for solving the subproblems during sifting.
HeurEmphasis	8,427	Branch and Bound: This control specifies an emphasis for the search w.r.t. primal heuristics and other procedures that affect the speed of convergence of the primal-dual gap. For problems where the goal is to achieve a small gap but not neccessarily solving them to optimality, it is recommended to set HEUREMPHASIS to 1. This setting triggers many additional heuristic calls, aiming for reducing the gap at the beginning of the search, typically at the expense of an increased time for proving optimality.
BarRefIter	8,431	Newton barrier: After terminating the barrier algorithm, further refinement steps can be performed. Such refinement steps are especially helpful if the solution is near to the optimum and can improve primal feasibility and decrease the complementarity gap. It is also often advantageous for the crossover algorithm. BARREFITER specifies the maximum number of such refinement iterations.
ComputeLog	8,434	Controls how the run log is fetched when a solve is performed on an Insight Compute Interface.
SiftPresolveOps	8,435	Determines the presolve operations for solving the subproblems during the sifting algorithm.
CheckInputData	8,436	Check input arrays for bad data.
EscapeNames	8,440	If characters illegal to an mps or lp file should be escaped to guarantee readability, and whether escaped characters should be transformed back when reading such a file.
IOTimeout	8,442	The maximum number of seconds to wait for an I/O operation before it is cancelled.
MaxStallTime	8,443	The maximum time in seconds that the Optimizer will continue to search for improving solution after finding a new incumbent.
AutoCutting	8,446	Should the Optimizer automatically decide whether to generate cutting planes at local nodes in the tree or not? If the CUTFREQ control is set, no automatic selection will be made and local cutting will be enabled.
GlobalNumInitNlpCuts	8,449	Specifies the maximum number of tangent cuts when setting up the initial relaxation during a global solve. By default, the algorithm chooses the number of cuts automatically. Adding more cuts tightens the problem, resulting in a smaller branch-and-bound tree, at the cost of slowing down each LP solve.
CallbackCheckTimeDelay	8,451	Minimum delay in milliseconds between two consecutive executions of the CHECKTIME callback in the same solution process
MultiObjOps	8,457	Modifies the behaviour of the optimizer when solving multi-objective problems.
MultiObjLog	8,458	Log level for multi-objective optimization.
BackgroundMaxThreads	8,461	Limit the number of threads to use in background jobs (for example in parallel to the root cut loop).
BackgroundSelect	8,463	Bit-vector control (see Section ) to select which tasks to run in background jobs (for example in parallel to the root cut loop).
GlobalLSHeurstrategy	8,464	When integer-feasible (for MINLP, any solution for NLP) but nonlinear-infeasible solutions are encountered within a global solve, the integer variables can be fixed and a local solver (as defined by the LOCALSOLVER control) can be called on the remaining continuous problem. This control defines the frequency and effort of such local solves.
GlobalSpatialBranchIfPreferOrig	8,465	Whether spatial branchings on original variables should be preferred over branching on auxiliary variables that were introduced by the reformulation of the global solver.
PreConfiguration	8,470	MIP Presolve: determines whether binary rows with only few repeating coefficients should be reformulated. The reformulation enumerates the extremal feasible configurations of a row and introduces new columns and rows to model the choice between these extremal configurations. This presolve operation can be disabled as part of the (advanced) IP reductions PRESOLVEOPS.
FeasibilityJump	8,471	MIP: Decides if the Feasibility Jump heuristic should be run. The value for this control is either -1 (let Xpress decide), 0 (off) or a value that indicates for which type of models the heuristic should be run.
IISOps	8,472	Selects which part of the restrictions (bounds, constraints, entities) should always be kept in an IIS. This is useful if certain types of restrictions cannot be violated, thus they are known not to be the cause of infeasibility. The IIS obtained this way is irreducible only for the non-protected restrictions. This bit-vector control (see Section ) has an effect only on the deletion filter of the IIS procedure.
RLTCuts	8,476	Determines whether RLT cuts should be separated in the Xpress Global Solver.
HeursearchBackgroundSelect	8,477	Bit-vector control (see Section ) to select which large neighborhood searches to run in the background (for example in parallel to the root cut loop).
AlternativeRedCosts	8,478	Controls aggressiveness of searching for alternative reduced cost
HeurShiftProp	8,479	Determines whether the Shift-and-propagate primal heuristic should be executed. If enabled, Shift-and-propagate is an LP-free primal heuristic that is executed immediately after presolve.
HeurSearchCopyControls	8,480	Select how user-set controls should affect local search heuristics.
GlobalNlpCuts	8,481	Limit on the number of rounds of outer approximation and convexification cuts generated for the root node, when solving an (MI)NLP to global optimality.
GlobalTreeNlpCuts	8,482	Limit on the number of rounds of outer approximation and convexification cuts generated for each node in the tree, when solving an (MI)NLP to global optimality.
BarhgOps	8,483	Bit-vector control (see Section ) options for the hybrid gradient algorithm. Bits 1, 2 and 3 control which norms of the coefficient matrix are used for solution normalization. The normalization factor is the maximum of the selected norms. By default, or if all three bits are set to 0, the infinity norm is used. The omega parameter referenced in bits 4, 5 and 6 is a measure of the relative magnitudes of the objective and the right-hand side.
BarhgMaxRestarts	8,484	The maximum number of restarts in the hybrid gradient algorithm. Restarts play the role of iterations in the hybrid gradient algorithm. A log line is printed at every restart, unless BAROUTPUT is set to 0.
MCFCutStrategy	8,486	Level of Multi-Commodity Flow (MCF) cutting planes separation: This specifies how much aggresively MCF cuts should be separated. If the separation of MCF cuts is enabled, Xpress will try to detect a MCF network structure in the problem and, if such a structure is identified, it will separate specific cutting planes exploiting the identified network.
PreRootThreads	8,490	Specifies an explicit number of threads that should be used for the Pre-root parallel heuristic phase. By default, this phase will use all threads available to the solver (as governed by the control THREADS).
BarIterative	8,492	The maximum number of barrier iterations in which an iterative solver is used instead of the Cholesky decomposition.
SlpDamp	12,103	Damping factor for updating values of variables
SlpDampExpand	12,104	Multiplier to increase damping factor during dynamic damping
SlpDampShrink	12,105	Multiplier to decrease damping factor during dynamic damping
SlpDelta_A	12,106	Absolute perturbation of values for calculating numerical derivatives
SlpDelta_R	12,107	Relative perturbation of values for calculating numerical derivatives
SlpDelta_Z	12,108	Tolerance used when calculating derivatives
SlpDeltaCost	12,109	Initial penalty cost multiplier for penalty delta vectors
SlpDeltaMaxCost	12,110	Maximum penalty cost multiplier for penalty delta vectors
SlpDJTol	12,112	Tolerance on DJ value for determining if a variable is at its step bound
SlpErrorCost	12,113	Initial penalty cost multiplier for penalty error vectors
SlpErrorMaxCost	12,114	Maximum penalty cost multiplier for penalty error vectors
SlpErrorTol_A	12,116	Absolute tolerance for error vectors
SlpExpand	12,118	Multiplier to increase a step bound
NlpInfinity	12,119	Value returned by a divide-by-zero in a formula
SlpMaxWeight	12,120	Maximum penalty weight for delta or error vectors
SlpMinWeight	12,121	Minimum penalty weight for delta or error vectors
SlpShrink	12,122	Multiplier to reduce a step bound
NlpZero	12,123	Absolute tolerance
SlpCTol	12,124	Closure convergence tolerance
SlpATol_A	12,125	Absolute delta convergence tolerance
SlpATol_R	12,126	Relative delta convergence tolerance
SlpMTol_A	12,127	Absolute effective matrix element convergence tolerance
SlpMTol_R	12,128	Relative effective matrix element convergence tolerance
SlpItol_A	12,129	Absolute impact convergence tolerance
SlpITol_R	12,130	Relative impact convergence tolerance
SlpSTol_A	12,131	Absolute slack convergence tolerance
SlpSTol_R	12,132	Relative slack convergence tolerance
SlpMVTol	12,133	Marginal value tolerance for determining if a constraint is slack
SlpXTol_A	12,134	Absolute static objective function (1) tolerance
SlpXTol_R	12,135	Relative static objective function (1) tolerance
SlpDefaultStepBound	12,136	Minimum initial value for the step bound of an SLP variable if none is explicitly given
SlpDampMax	12,137	Maximum value for the damping factor of a variable during dynamic damping
SlpDampMin	12,138	Minimum value for the damping factor of a variable during dynamic damping
SlpDeltaCostFactor	12,139	Factor for increasing cost multiplier on total penalty delta vectors
SlpErrorCostFactor	12,140	Factor for increasing cost multiplier on total penalty error vectors
SlpErrorTol_P	12,141	Absolute tolerance for printing error vectors
SlpCascadeTol_PA	12,142	Absolute cascading print tolerance
SlpCascadeTol_PR	12,143	Relative cascading print tolerance
NlpDefaultIV	12,145	Default initial value for an SLP variable if none is explicitly given
SlpOTol_A	12,150	Absolute static objective (2) convergence tolerance
SlpOTol_R	12,151	Relative static objective (2) convergence tolerance
SlpDelta_X	12,152	Minimum absolute value of delta coefficients to be retained
SlpGranularity	12,157	Base for calculating penalty costs
SlpMipCutoff_A	12,158	Absolute objective function cutoff for MIP termination
SlpMipCutoff_R	12,159	Absolute objective function cutoff for MIP termination
SlpMipOtol_A	12,160	Absolute objective function tolerance for MIP termination
SlpMipOtol_R	12,161	Relative objective function tolerance for MIP termination
NlpValidationTol_A	12,165	Absolute tolerance for the XSLPvalidate procedure
NlpValidationTol_R	12,166	Relative tolerance for the XSLPvalidate procedure
SlpEscalation	12,169	Factor for increasing cost multiplier on individual penalty error vectors
SlpObjToPenaltyCost	12,170	Factor to estimate initial penalty costs from objective function
SlpShrinkBias	12,171	Defines an overwrite / adjustment of step bounds for improving iterations
SlpFeastolTarget	12,172	When set, this defines a target feasibility tolerance to which the linearizations are solved to
SlpOptimalityTolTarget	12,173	When set, this defines a target optimality tolerance to which the linearizations are solved to
SlpDelta_Infinity	12,174	Maximum value for partial derivatives
NlpPrimalIntegralRef	12,175	Reference solution value to take into account when calculating the primal integral
NlpPrimalIntegralAlpha	12,176	Decay term for primal integral computation
SlpVTol_A	12,177	Absolute static objective (3) convergence tolerance
SlpVTol_R	12,178	Relative static objective (3) convergence tolerance
SlpETol_A	12,180	Absolute tolerance on penalty vectors
SlpETol_R	12,181	Relative tolerance on penalty vectors
SlpEVTol_A	12,182	Absolute tolerance on total penalty costs
SlpEVTol_R	12,183	Relative tolerance on total penalty costs
SlpDelta_Zero	12,184	Absolute zero acceptance tolerance used when calculating derivatives
SlpMinSBFactor	12,185	Factor by which step bounds can be decreased beneath XSLP_ATOL_A
SlpClampValidationTol_A	12,186	Absolute validation tolerance for applying XSLP_CLAMPSHRINK
SlpClampValidationTol_R	12,187	Relative validation tolerance for applying XSLP_CLAMPSHRINK
SlpClampShrink	12,188	Shrink ratio used to impose strict convergence on variables converged in extended criteria only
SlpEcfTol_A	12,189	Absolute tolerance on testing feasibility at the point of linearization
SlpEcfTol_R	12,190	Relative tolerance on testing feasibility at the point of linearization
SlpWTol_A	12,191	Absolute extended convergence continuation tolerance
SlpWTol_R	12,192	Relative extended convergence continuation tolerance
NlpPresolveZero	12,193	Minimum absolute value for a variable which is identified as nonzero during SLP presolve
SlpMatrixTol	12,194	Nonzero tolerance for dropping coefficients from the linearization.
SlpDRFixRange	12,195	The range around the previous value where variables are fixed in cascading if the determining column is below XSLP_DRCOLTOL.
SlpDRColTol	12,196	The minimum absolute magnitude of a determining column, for which the determined variable is still regarded as well defined
NlpMeritLambda	12,197	Factor by which the net objective is taken into account in the merit function
SlpMipErrorTol_A	12,198	Absolute penalty error cost tolerance for MIP cut-off
SlpMipErrorTol_R	12,199	Relative penalty error cost tolerance for MIP cut-off
SlpCDTol_A	12,200	Absolute tolerance for deducing constant derivatives
SlpCDTol_R	12,201	Relative tolerance for deducing constant derivatives
SlpEnforceMaxCost	12,202	Maximum penalty cost in the objective before enforcing most violating rows
SlpEnforceCostShrink	12,203	Factor by which to decrease the current penalty multiplier when enforcing rows.
MsMaxBoundRange	12,204	Defines the maximum range inside which initial points are generated by multistart presets
NlpValidationTol_K	12,205	Relative tolerance for the XSLPvalidatekkt procedure
NlpPresolve_ElimTol	12,206	Tolerance for nonlinear eliminations during SLP presolve
SlpDRColDjTol	12,208	Reduced cost tolerance on the delta variable when fixing due to the determining column being below XSLP_DRCOLTOL.
NlpValidationTarget_R	12,209	Feasiblity target tolerance
NlpValidationTarget_K	12,210	Optimality target tolerance
NlpValidationFactor	12,211	Minimum improvement in validation targets to continue iterating
SlpBarStallingTol	12,212	Required change in the objective when progress is measured in barrier iterations without crossover
SlpObjThreshold	12,213	Assumed maximum value of the objective function in absolute value.
SlpBoundThreshold	12,214	The maximum size of a bound that can be introduced by nonlinear presolve.
SlpAlgorithm	12,301	Bit map describing the SLP algorithm(s) to be used
SlpAugmentation	12,302	Bit map describing the SLP augmentation method(s) to be used
SlpBarLimit	12,303	Number of initial SLP iterations using the barrier method
SlpCascade	12,304	Bit map describing the cascading to be used
SlpCascadeNLimit	12,306	Maximum number of iterations for cascading with non-linear determining rows
SlpDampStart	12,308	SLP iteration at which damping is activated
SlpCutStrategy	12,310	Determines whihc cuts to apply in the MISLP search when the default SLP-in-MIP strategy is used.
SlpDeltaZLimit	12,311	Number of SLP iterations during which to apply XSLP_DELTA_Z
NlpFuncEval	12,312	Bit map for determining the method of evaluating user functions and their derivatives
SlpInfeasLimit	12,314	The maximum number of consecutive infeasible SLP iterations which can occur before Xpress-SLP terminates
SlpIterLimit	12,315	The maximum number of SLP iterations
NlpLog	12,316	Level of printing during SLP iterations
SlpSameCount	12,317	Number of steps reaching the step bound in the same direction before step bounds are increased
SlpSameDamp	12,319	Number of steps in same direction before damping factor is increased
SlpSBStart	12,320	SLP iteration after which step bounds are first applied
SlpXCount	12,321	Number of SLP iterations over which to measure static objective (1) convergence
SlpXLimit	12,322	Number of SLP iterations up to which static objective (1) convergence testing is performed
SlpDelayUpdateRows	12,329	Number of SLP iterations before update rows are fully activated
SlpAutoSave	12,330	Frequency with which to save the model
SlpAnalyze	12,332	Bit map activating additional options supporting model / solution path analysis
SlpOCount	12,333	Number of SLP iterations over which to measure objective function variation for static objective (2) convergence criterion
NlpEvaluate	12,334	Evaluation strategy for user functions
SlpMipAlgorithm	12,336	Bitmap describing the MISLP algorithms to be used
SlpMipRelaxStepBounds	12,337	Bitmap describing the step-bound relaxation strategy during MISLP
SlpMipFixStepBounds	12,338	Bitmap describing the step-bound fixing strategy during MISLP
SlpMipIterLimit	12,339	Maximum number of SLP iterations at each node
SlpMipCutoffLimit	12,340	Number of SLP iterations to check when considering a node for cutting off
SlpMipOCount	12,341	Number of SLP iterations at each node over which to measure objective function variation
SlpMipDefaultAlgorithm	12,343	Default algorithm to be used during the tree search in MISLP
NlpPresolve	12,344	This control determines whether presolving should be performed on the nonlinear problem prior to starting the main algorithm
SlpMipLog	12,347	Frequency with which MIP status is printed
SlpDeltaOffset	12,348	Position of first character of SLP variable name used to create name of delta vector
SlpUpdateOffset	12,349	Position of first character of SLP variable name used to create name of SLP update row
SlpErrorOffset	12,350	Position of first character of constraint name used to create name of penalty error vectors
SlpSBRowOffset	12,351	Position of first character of SLP variable name used to create name of SLP lower and upper step bound rows
LocalSolver	12,352	Selects the library to use for local solves
NlpStopOutOfRange	12,354	Stop optimization and return error code if internal function argument is out of range
SlpVCount	12,356	Number of SLP iterations over which to measure static objective (3) convergence
SlpVLimit	12,357	Number of SLP iterations after which static objective (3) convergence testing starts
NlpThreadSafeUserFunc	12,359	Defines if user functions are allowed to be called in parallel
NlpJacobian	12,360	First order differentiation mode when using analytical derivatives
NlpHessian	12,361	Second order differentiation mode when using analytical derivatives
MultiStart	12,362	The multistart master control. Defines if the multistart search is to be initiated, or if only the baseline model is to be solved.
MultiStart_Threads	12,363	The maximum number of threads to be used in multistart
MultiStart_MaxSolves	12,364	The maximum number of jobs to create during the multistart search.
MultiStart_MaxTime	12,365	The maximum total time to be spent in the mutlistart search.
NlpMaxTime	12,366	The maximum time in seconds that the SLP optimization will run before it terminates
SlpECFCheck	12,369	Check feasibility at the point of linearization for extended convergence criteria
SlpMipCutOffCount	12,370	Number of SLP iterations to check when considering a node for cutting off
NlpDerivatives	12,373	Bitmap describing the method of calculating derivatives
SlpWCount	12,374	Number of SLP iterations over which to measure the objective for the extended convergence continuation criterion
SlpUnFinishedLimit	12,376	The number of consecutive SLP iterations that may have an unfinished status before the solve is terminated.
SlpConvergenceOps	12,377	Bit map describing which convergence tests should be carried out
SlpZeroCriterion	12,378	Bitmap determining the behavior of the placeholder deletion procedure
SlpZeroCriterionStart	12,379	SLP iteration at which criteria for deletion of placeholder entries are first activated.
SlpZeroCriterionCount	12,380	Number of consecutive times a placeholder entry is zero before being considered for deletion
SlpLSPatternLimit	12,381	Number of iterations in the pattern search preceding the line search
SlpLSIterLimit	12,382	Number of iterations in the line search
SlpLSStart	12,383	Iteration in which to active the line search
SlpPenaltyInfoStart	12,384	Iteration from which to record row penalty information
SlpFilter	12,387	Bit map for controlling solution updates
SlpTraceMaskOps	12,388	Controls the information printed for XSLP_TRACEMASK. The order in which the information is printed is determined by the order of bits in XSLP_TRACEMASKOPS.
SlpLSZeroLimit	12,389	Maximum number of zero length line search steps before line search is deactivated
NlpReformulate	12,392	Controls the problem reformulations carried out before augmentation. This allows SLP to take advantage of dedicated algorithms for special problem classes.
NlpPresolveOps	12,393	Bitmap indicating the SLP presolve actions to be taken
MultiStart_Log	12,395	The level of logging during the multistart run.
MultiStart_Seed	12,396	Random seed used for the automatic generation of initial point when loading multistart presets
MultiStart_PoolSize	12,397	The maximum number of problem objects allowed to pool up before synchronization in the deterministic multistart.
NlpPostsolve	12,398	This control determines whether postsolving should be performed automatically
NlpDeterministic	12,399	Determines if the parallel features of SLP should be guaranteed to be deterministic
SlpHeurStrategy	12,400	Branch and Bound: This specifies the MINLP heuristic strategy. On some problems it is worth trying more comprehensive heuristic strategies by setting HEURSTRATEGY to 2 or 3.
NlpPresolveLevel	12,402	This control determines the level of changes presolve may carry out on the problem and whether column/row indices may change
NlpProbing	12,403	This control determines whether probing on a subset of variables should be performed prior to starting the main algorithm. Probing runs multiple times bound reduction in order to further tighten the bounding box.
NlpCalcThreads	12,405	Number of threads used for formula and derivatives evaluations
NlpThreads	12,406	Default number of threads to be used
SlpBarCrossoverStart	12,408	Default crossover activation behaviour for barrier start
SlpBarStallingLimit	12,409	Number of iterations to allow numerical failures in barrier before switching to dual
SlpBarStallingObjLimit	12,410	Number of iterations over which to measure the objective change for barrier iterations with no crossover
SlpBarStartOps	12,411	Controls behaviour when the barrier is used to solve the linearizations
SlpGridHeurSelect	12,412	Bit map selectin which heuristics to run if the problem has variable with an integer delta
NlpFindIV	12,413	Option for running a heuristic to find a feasible initial point
NlpLinQuadBR	12,414	Use linear and quadratic constraints and objective function to further reduce bounds on all variables
NLPSolver	12,417	Controls whether to call FICO Xpress Global or one of the local solvers
KnitroParamNewPoint	101,001
KnitroParamHonorBbnds	101,002	Indicates whether or not to enforce satisfaction of simple variable bounds throughout the optimization.
KnitroParamAlgorithm	101,003	Indicates which algorithm to use to solve the problem
KnitroParamBarMuRule	101,004	Indicates which strategy to use for modifying the barrier parameter mu in the barrier algorithms.
KnitroParamBarFeasible	101,006	Specifies whether special emphasis is placed on getting and staying feasible in the interior-point algorithms.
KnitroParamGradOpt	101,007	Specifies how to compute the gradients of the objective and constraint functions.
KnitroParamHessOpt	101,008	Specifies how to compute the (approximate) Hessian of the Lagrangian.
KnitroParamBarInitPt	101,009	Indicates whether an initial point strategy is used with barrier algorithms.
KnitroParamMaxCGIt	101,013	Specifies the number of limited memory pairs stored when approximating the Hessian using the limited-memory quasi-Newton BFGS option.
KnitroParamMaxIt	101,014	Specifies the maximum number of iterations before termination.
KnitroParamOutLev	101,015	Controls the level of output produced by Knitro.
KnitroParamScale	101,017	Performs a scaling of the objective and constraint functions based on their values at the initial point.
KnitroParamSOC	101,019	Specifies whether or not to try second order corrections (SOC).
KnitroParamDelta	101,020	Specifies the initial trust region radius scaling factor used to determine the initial trust region size.
KnitroParamBarFeasModeTol	101,021	Specifies the tolerance in equation that determines whether Knitro will force subsequent iterates to remain feasible.
KnitroParamFeastol	101,022	Specifies the final relative stopping tolerance for the feasibility error.
KnitroParamFeasTolAbs	101,023	Specifies the final absolute stopping tolerance for the feasibility error.
KnitroParamBarInitMu	101,025	Specifies the initial value for the barrier parameter : mu used with the barrier algorithms. This option has no effect on the Active Set algorithm.
KnitroParamObjRange	101,026	Specifies the extreme limits of the objective function for purposes of determining unboundedness.
KnitroParamOptTol	101,027	Specifies the final relative stopping tolerance for the KKT (optimality) error.
KnitroParamOptTolAbs	101,028	Specifies the final absolute stopping tolerance for the KKT (optimality) error.
KnitroParamPivot	101,029
KnitroParamXTol	101,030	The optimization process will terminate if the relative change in all components of the solution point estimate is less than xtol.
KnitroParamDebug	101,031
KnitroParamMultiStart	101,033
KnitroParamMSMaxSolves	101,034
KnitroParamMsMaxBndRange	101,035
KnitroParamLMSize	101,038	Specifies the number of limited memory pairs stored when approximating the Hessian using the limited-memory quasi-Newton BFGS option.
KnitroParamMaxCrossIt	101,039	Specifies the maximum number of crossover iterations before termination.
KnitroParamBLASOption	101,042
KnitroParamBarMaxRefactor	101,043	Indicates the maximum number of refactorizations of the KKT system per iteration of the Interior/Direct algorithm before reverting to a CG step.
KnitroParamBarMaxBacktrack	101,044	Indicates the maximum allowable number of backtracks during the linesearch of the Interior/Direct algorithm before reverting to a CG step.
KnitroParamBarPenRule	101,049	Indicates which penalty parameter strategy to use for determining whether or not to accept a trial iterate.
KnitroParamBarPenCons	101,050	Indicates whether a penalty approach is applied to the constraints.
KnitroParamMSNumToSave	101,051
KnitroParamMSSaveTol	101,052
KnitroParamMSTerminate	101,054
KnitroParamMSStartPtRange	101,055
KnitroParamInfeasTol	101,056	Specifies the (relative) tolerance used for declaring infeasibility of a model.
KnitroParamLinSolver	101,057
KnitroParamBarDirectInterval	101,058	Controls the maximum number of consecutive conjugate gradient (CG) steps before Knitro will try to enforce that a step is taken using direct linear algebra.
KnitroParamPresolve	101,059	Determine whether or not to use the Knitro presolver to try to simplify the model by removing variables or constraints. Specifies conditions for terminating the MIP algorithm.
KnitroParamPresolveTol	101,060	Determines the tolerance used by the Knitro presolver to remove variables and constraints from the model.
KnitroParamBarSwitchRule	101,061	Indicates whether or not the barrier algorithms will allow switching from an optimality phase to a pure feasibility phase.
KnitroParamMATerminate	101,063
KnitroParamMSSeed	101,066
KnitroParamBarRelaxCons	101,077
KnitroParamMIPMethod	102,001	Specifies which MIP method to use.
KnitroParamMIPBranchRule	102,002	Specifies which branching rule to use for MIP branch and bound procedure.
KnitroParamMIPSelectRule	102,003	Specifies the MIP select rule for choosing the next node in the branch and bound tree.
KnitroParamMIPIntGapAbs	102,004	The absolute integrality gap stop tolerance for MIP.
KnitroParamMIPIntGapRel	102,005	The relative integrality gap stop tolerance for MIP.
KnitroParamMIPOutLevel	102,010	Specifies how much MIP information to print.
KnitroParamMIPOutInterval	102,011	Specifies node printing interval for XKTR_PARAM_MIP_OUTLEVEL when XKTR_PARAM_MIP_OUTLEVEL > 0.
KnitroParamMIPDebug	102,013
KnitroParamMIPImplicatns	102,014	Specifies whether or not to add constraints to the MIP derived from logical implications.
KnitroParamMIPGUBBranch	102,015	Specifies whether or not to branch on generalized upper bounds (GUBs).
KnitroParamMIPKnapsack	102,016	Specifies rules for adding MIP knapsack cuts.
KnitroParamMIPRounding	102,017	Specifies the MIP rounding rule to apply.
KnitroParamMIPRootAlg	102,018	Specifies which algorithm to use for the root node solve in MIP (same options as XKTR_PARAM_ALGORITHM user option).
KnitroParamMIPLPAlg	102,019	Specifies which algorithm to use for any linear programming (LP) subproblem solves that may occur in the MIP branch and bound procedure.
KnitroParamMIPMaxNodes	102,021	Specifies the maximum number of nodes explored.
KnitroParamMIPHeuristic	102,022	Specifies which MIP heuristic search approach to apply to try to find an initial integer feasible point.
KnitroParamMIPHeurMaxIt	102,023
KnitroParamMIPPseudoint	102,026	Specifies the method used to initialize pseudo-costs corresponding to variables that have not yet been branched on in the MIP method.
KnitroParamMIPStringMaxIt	102,027	Specifies the maximum number of iterations to allow for MIP strong branching solves.
KnitroParamMIPStrongCandLim	102,028	Specifies the maximum number of candidates to explore for MIP strong branching.
KnitroParamMIPStrongLevel	102,029	Specifies the maximum number of tree levels on which to perform MIP strong branching.
KnitroParamParNumThreads	103,001

Reference

Optimizer Namespace

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Contents

Index

Glossary

Search Results

XPRScontrol Enumeration

Reference