def run(self):
# Wait 5 seconds ...
time.sleep(5)
# ... and abort the CPLEX optimization.
print("Aborting CPLEX via a cplex.terminate() call.")
cplex.terminate()
def run(self):
# Wait 5 seconds ...
time.sleep(5)
# ... and abort the CPLEX optimization.
print "Aborting CPLEX via a cplex.terminate() call."
cplex.terminate()
dense.parameters.lpmethod.set(alg.barrier)
dense.parameters.barrier.crossover.set(-1)
start_time = dense.get_time()
dense.solve()
end_time = dense.get_time()
iter_time = end_time - start_time
times.append(iter_time)
#TODO: check if feasible, if not divide the scalar by 2.
if(dense.solution.get_status() == dense.solution.status.infeasible_or_unbounded):
print "infeasible solution."
scalar = scalar * 0.5
lamda = oldlamda[:]
else:
j += 1
if scalar < 0.01:
break
prev_t = dense.solution.get_values(0)
prev_xijm = dense.solution.get_values(range(1,len(xijm)))
prev_val = dense.solution.get_objective_value()
print "Iteration "+str(j)+" ("+str(iter_time)+" sec.): "+str(prev_val)
total_time = sum(times)
print "Total time: " + str(total_time) + " sec."
printResults.save(dense)
cplex.terminate()
os.remove("dense.lp")