Initializing help system before first use

xprsmip

xprsmip

Purpose
Solve mixed integer linear programming problems with Xpress.
Synopsis
x = xprsmip(f,A,b,rtype,ctype, clim,sos,lb,ub,x0,options)
[x,fval,exitflag,output] = xprsmip(...)
Input arguments
f 
Linear objective function vector
A 
Matrix for linear constraints
b 
Vector for constraints RHS
rtype 
Character vector (string) giving the row types:
L 
indicates a ≤ row
E 
indicates a = row
G 
indicates a ≥ row
N 
indicates a free row
If rtype = [], all rows are assumed to be of type 'L'. If rtype is a single character, all constraints are assigned the corresponding type.
ctype 
Character vector (string) giving the column types:
C 
(or \0) continuous variables
B 
binary variables
I 
integer variables
P 
partial integer variables
S 
semi-continuous variables
R 
semi-continuous integers
If ctype = [], all rows are assumed to be of type 'C'. If ctype is a single character, all constraints are assigned the corresponding type.
clim 
Vector containing the integer limits for the partial integer variables and lower bounds for semi-continuous and semi-continuous integer variables (column types 'P', 'S', 'R'). Values in the positions corresponding to all other columns are ignored. clim is mandatory if there are any 'P', 'S', or 'R' columns. If clim is a scalar, all columns are assigned to that same limit.
sos 
Struct vector defining SOS sets. The number of SOS sets is given by the number of elements in the struct. The struct must contain the following fields:
sos(i).type 
a character indicating the SOS type, either '1' or '2'
sos(i).ind 
numeric vector with the indices of columns in the set (column indices start from 0)
sos(i).wt 
numeric vector with the reference row weights corresponding to the columns in the sos(i).ind vector. It must have the same length as sos(i).ind
lb 
Lower bounds. If lb = [] it means there are no lower bounds. If lb is a scalar, x is uniformly bounded by that scalar.
ub 
Upper bounds. If ub = [] it means there are no upper bounds. If ub is a scalar, x is uniformly bounded by that scalar.
x0 
Optional initial known solution used to speed-up search.
options 
Options structure created with optimset or xprsoptimset functions. See xprsoptimset for more details.
Output arguments
x 
Solution found by the optimization function. If exitflag > 0, then x is a solution; otherwise, x is the value of the optimization routine when it terminated prematurely.
fval 
Value of the objective function at the solution x.
exitflag 
Integer identifying the reason the optimization algorithm terminated. The following lists the values of exitflag and the corresponding reasons the algorithm terminated.
1 
function converged to a solution x (MIPSTATUS=MIP_OPTIMAL)
0 
number of iterations exceeded iter limit (STOPSTATUS= STOP_ITERLIMIT)
-2 
the problem is infeasible (MIPSTATUS=MIP_INFEAS)
-4 
number of searched nodes exceeded limit (STOPSTATUS= STOP_NODELIMIT)
-5 
search time exceeded limit (STOPSTATUS= STOP_TIMELIMIT)
-8 
other stop reason, see MIPSTATUS and STOPSTATUS for details
output 
Structure containing information about the optimization and, eventually, values of Xpress controls and attributes. See linprog and the Section Setting and querying controls and attributes for details.
Further information
1. This routine finds the minimum of a problem specified by
min f·x
s.t. A·x ≤|=|≥ b   
lb≤ x ≤ ub
where A is an m × n matrix; f, b, rtype, ctype, clim, lb, ub, and x0 are vectors; sos is a struct vector.
2. Input arguments rtype and following can be omitted, with the condition that, if one is omitted, also all the following ones must be omitted (as in x=xprsmip(f, A, b, rtype)). Omitting an input argument has the same effect as passing an empty array [].
3. All output arguments can be omitted too, again with the condition that, if one is omitted, also all the following ones must be omitted (as in [x, fval]= xprsmip(f, A, b, rtype)).
4. If the specified input bounds for a problem are inconsistent, the output x and fval are set to [].
Related topics
xprsoptimset, bintprog

Parent Topic Xpress MATLAB functions

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