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

150 CHAPTER 11. THE OPTIMIZERS FOR CONTINUOUS PROBLEMS
Optimizer Associated Default
parameter
priority
optimizertype.intpnt iparam.concurrent priority intpnt 4
optimizertype.free simplex iparam.concurrent priority free simplex 3
optimizertype.primal simplex iparam.concurrent priority primal simplex 2
optimizertype.dual simplex iparam.concurrent priority dual simplex 1
Table 11.4: Default priorities for optimizer selection in concurrent optimization.
11.6.3.1 Concurrent optimization through the API
The following example shows how to call the concurrent optimizer through the API.
##
# Copyright: Copyright (c) MOSEK ApS, Denmark. All rights reserved.
#
# File: concurrent1.py
#
# Purpose: To demonstrate how to optimize in parallel using the
# concurrent optimizer.
##
import sys
import mosek
from mosek.array import array
# Since the actual value of Infinity is ignores, we define it solely
# for symbolic purposes:
inf = 0.0
# Define a stream printer to grab output from MOSEK
def streamprinter(text):
sys.stdout.write(text)
sys.stdout.flush()
# We might write everything directly as a script, but it looks nicer
# to create a function.
def main (args):
# Open MOSEK and create an environment and task
# Create a MOSEK environment
env = mosek.Env ()
# Attach a printer to the environment
env.set Stream (mosek.streamtype.log, streamprinter)
# Create a task
task = env.Task(0,0)
# Attach a printer to the task
task.set Stream (mosek.streamtype.log, streamprinter)