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

66 CHAPTER 5. BASIC API TUTORIAL
and
x 0 , x 1 , x 2 , x 3 ≥ 0.
5.10.4 Reoptimization
When
Task.optimize is called MOSEK will store the optimal solution internally. After a task has been
modified and
Task.optimize is called again the solution will automatically be used to reduce solution time of the
new problem, if possible.
In this case an optimal solution to problem (5.11) was found and then added a column was added
to get (5.12). The simplex optimizer is well suited for exploiting an existing primal or dual feasible
solution. Hence, the subsequent code instructs MOSEK to choose the simplex optimizer freely when
optimizing.
[ production.py ]
142 # Change optimizer to simplex free and reoptimize
143 task.putintparam(mosek.iparam.optimizer,mosek.optimizertype.free simplex)
144 task.optimize()
5.10.5 Appending constraints
Now suppose we want to add a new stage to the production called ”Quality control” for which 30000
minutes are available. The time requirement for this stage is shown below:
This corresponds to adding the constraint
Product no. Quality control (minutes)
0 1
1 2
2 1
3 1
x 0 + 2x 1 + x 2 + x 3 ≤ 30000
to the problem which is done in the following code:
145 # Append a new constraint
146 task.appendcons(1)
147
[ production.py ]
148 # Set bounds on new constraint
149 task.putconbound( task.getnumcon()-1, mosek.boundkey.up,-inf, 30000)
150