mosek_linear_programming_quickstart_maximization_example.py

1import sys
2import mosek
3
4# Define a stream printer to display log information
5def streamprinter(text):
6    sys.stdout.write(text)
7    sys.stdout.flush()
8
9def main():
10    # Make a MOSEK environment
11    with mosek.Env() as env:
12        # Create an optimization task
13        with env.Task(0, 0) as task:
14            # Attach a log stream printer to the task
15            task.set_Stream(mosek.streamtype.log, streamprinter)
16
17            # Bound keys for constraints
18            # bkp: constraint bound keys (Lower, Upper, Fixed, Free, Range)
19            # blp: lower bounds
20            # bup: upper bounds
21            bkp = [mosek.boundkey.up, mosek.boundkey.up, mosek.boundkey.up]
22            blp = [-float('inf'), -float('inf'), -float('inf')]
23            bup = [30.0, 12.0, 20.0]
24
25            # Bound keys for variables
26            # bkx: variable bound keys
27            # blx: lower bounds
28            # bux: upper bounds
29            bkx = [mosek.boundkey.lo, mosek.boundkey.lo, mosek.boundkey.lo, mosek.boundkey.lo]
30            blx = [0.0, 0.0, 0.0, 0.0]
31            bux = [float('inf'), float('inf'), float('inf'), float('inf')]
32
33            # Objective coefficients
34            c = [3.0, 1.0, 5.0, 1.0]
35
36            # Constraint matrix in sparse format (column-wise)
37            asub = [[0, 1], [0, 1, 2], [0, 2], [1, 2]]
38            aval = [[3.0, 1.0], [1.0, 2.0, 1.0], [2.0, 1.0], [1.0, 3.0]]
39
40            numvar = len(bkx)
41            numcon = len(bkp)
42
43            # Append 'numcon' empty constraints.
44            task.appendcons(numcon)
45
46            # Append 'numvar' empty variables.
47            task.appendvars(numvar)
48
49            for j in range(numvar):
50                # Set the linear objective coefficient c_j
51                task.putcj(j, c[j])
52                # Set the bounds on variable x_j
53                task.putvarbound(j, bkx[j], blx[j], bux[j])
54                # Input column j of A
55                task.putacol(j, asub[j], aval[j])
56
57            for i in range(numcon):
58                # Set the bounds on constraints
59                task.putconbound(i, bkp[i], blp[i], bup[i])
60
61            # Input the objective sense (maximize/minimize)
62            task.putobjsense(mosek.objsense.maximize)
63
64            # Solve the problem
65            task.optimize()
66
67            # Print a summary containing information about the solution for debugging purposes
68            task.solutionsummary(mosek.streamtype.msg)
69
70            # Get status information about the solution
71            solsta = task.getsolsta(mosek.soltype.bas)
72
73            if solsta == mosek.solsta.optimal:
74                xx = task.getxx(mosek.soltype.bas)
75                print("Optimal solution: %s" % xx)
76            elif solsta == mosek.solsta.dual_infeas_report or solsta == mosek.solsta.prim_infeas_report:
77                print("Infeasible or unbounded solution status")
78            elif solsta == mosek.solsta.unknown:
79                print("Unknown solution status")
80            else:
81                print("Other solution status")
82
83if __name__ == '__main__':
84    main()