The MOSEK Python optimizer API manual Version 7.0 (Revision 141)

5.7. INTEGER OPTIMIZATION 57
137 sys.exit(0)
5.7.1.2 Code comments
Please note that when Task.getsolutionslice is called, the integer solution is requested by using
soltype.itg. No dual solution is defined for integer optimization problems.
5.7.2 Specifying an initial solution
Integer optimization problems are generally hard to solve, but the solution time can often be reduced
by providing an initial solution for the solver. Solution values can be set using Task.putsolution (for
inputting a whole solution) or Task.putsolutioni (for inputting solution values related to a single
variable or constraint).
It is not necessary to specify the whole solution. By setting the iparam.mio construct sol parameter
to onoffkey.on and inputting values for the integer variables only, will force MOSEK to compute the
remaining continuous variable values.
If the specified integer solution is infeasible or incomplete, MOSEK will simply ignore it.
5.7.3 Example: Specifying an integer solution
Consider the problem
maximize 7x 0 + 10x 1 + x 2 + 5x 3
subject to x 0 + x 1 + x 2 + x 3 ≤ 2.5
x 0 , x 1 , x 2 integer , x 0 , x 1 , x 2 , x 3 ≥ 0
The following example demonstrates how to optimize the problem using a feasible starting solution
generated by selecting the integer values as x 0 = 0, x 1 = 2, x 2 = 0.
1 ##
[ mioinitsol.py ]
2 # Copyright: Copyright (c) MOSEK ApS, Denmark. All rights reserved.
3 #
4 # File: mioinitsol.py
5 #
6 # Purpose: Demonstrates how to solve a small mixed
7 # integer linear optimization problem using the MOSEK Python API.
8 ##
9
10 import sys
11
12 import mosek
13
14 # If numpy is installed, use that, otherwise use the
15 # Mosek’s array module.
16 try:
17 from numpy import array,zeros,ones