Initializing help system before first use

XPRSmaxim, XPRSminim (MAXIM, MINIM)

Purpose
This subroutine is deprecated and will be removed in a future release. XPRSlpoptimize or XPRSmipoptimize should be used instead.
Begins a search for the optimal LP solution.
Synopsis
int XPRS_CC XPRSmaxim(XPRSprob prob, const char *flags);
int XPRS_CC XPRSminim(XPRSprob prob, const char *flags);
MAXIM [-flags]
MINIM [-flags]
Arguments
prob 
The current problem.
flags 
Flags to pass to XPRSmaxim ( MAXIM) or XPRSminim ( MINIM). The default is "" or NULL, in which case the algorithm used is determined by the DEFAULTALG control. If the argument includes:
the problem will be solved using the Newton barrier method, or the Hybrid gradient method if BARALG is set to 4;
the problem will be solved using the primal simplex algorithm;
the problem will be solved using the dual simplex algorithm;
(lower case L), the problem will be solved as a linear problem ignoring the discreteness of MIP entities, unless the g flag is also provided (ref. note below);
(lower case N), the network part of the problem will be identified and solved using the network simplex algorithm;
the MIP problem will be solved by calling XPRSmipoptimize ( MIPOPTIMIZE).
Certain combinations of options may be used where this makes sense so, for example, pg will solve the LP with the primal algorithm and then go on to perform the tree search.
Related controls
Integer
Whether automatic perturbation is performed.
Maximum number of restarts for the hybrid gradient method.
Control options for the Hybrid gradient method.
Maximum number of Newton Barrier iterations.
Ordering algorithm for the Cholesky factorization.
Maximum number of threads for the ordering algorithm.
Newton barrier and hybrid gradient: level of solution output.
Newton barrier and hybrid gradient maximum number of threads to run on.
Specifies "Big M" method, or phaseI/phaseII.
Cache size in Kbytes for the Newton barrier.
1 for CPU time; 0 for elapsed time.
CRASH 
Type of crash.
Newton barrier and hybrid gradient crossover control.
Algorithm to use with the tree search.
Columns with this many elements are considered dense.
Pricing method for the dual algorithm.
Invert frequency.
Minimum number of iterations between inverts.
Whether to use previously loaded basis.
Iteration limit for the simplex algorithms.
LPLOG 
Frequency and type of simplex algorithm log.
Maximum time allowed.
Degree of presolving to perform.
Specifies the operations performed during presolve.
Type of pricing to be used.
Indicates whether to re-factorize the optimal basis.
TRACE 
Control of the infeasibility diagnosis during presolve.

Double
Newton barrier and hybrid gradient tolerance for dual infeasibilities.
Newton barrier and hybrid gradient tolerance for relative duality gap.
Extrapolation parameter for the hybrid gradient method.
Newton barrier and hybrid gradient tolerance for primal infeasibilities.
Newton barrier and hybrid gradient minimal step size.
BIGM 
Infeasibility penalty.
Tolerance in the Cholesky decomposition.
Dual perturbation value.
Markowitz tolerance for elimination phase of presolve.
ETATOL 
Tolerance on eta elements.
Tolerance on RHS.
Markowitz tolerance for the factorization.
Cutoff set after an LP Optimizer command. (Dual only)
Reduced cost tolerance.
Maximum absolute penalty variable coefficient.
Pivot tolerance.
Partial pricing candidate list sizing parameter.
Primal perturbation value.
Relative pivot tolerance.

Example 1 (Library)
XPRSmaxim(prob,"b");
This maximizes the current problem using the Newton barrier method.
Example 2 (Console)
MINIM -g
This minimizes the current problem and commences the tree search.
Further information
1. This function does not apply to general nonlinear problems and will solve the problem without the general nonlinearities.
2. The algorithm used to optimize is determined by the DEFAULTALG control. By default, the dual simplex is used for LP and MIP problems and the barrier is used for QP problems.
3. The d and p flags can be used with the n flag to complete the solution of the model with either the dual or primal algorithms once the network algorithm has solved the network part of the model.
4. The b flag cannot be used with the n flag.
5. The dual simplex algorithm is a two phase algorithm which can remove dual infeasibilities.
6. If both the g and l flags are used, the problem will be solved as a MIP and the l flag will be passed to XPRSmipoptimize, which will stop the solve after the initial LP relaxation has been solved.
7. ( Console) If the user prematurely terminates the solution process by typing CTRL-C, the iterative procedure will terminate at the first "safe" point.
Related topics

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