def optimize(self):
start = time.time()
clock = Clock()
clock.setStart(start)
if (self.DEBUG_MESSAGES):
print("=============================")
print("LNS Optimize Method Started...")
customerSubset = copy.deepcopy(self.customers)
facilitySubet = copy.deepcopy(self.facilities)
self.__InitializeProblem(facilitySubet, customerSubset)
self.__getQuantiles()
self.currentObjectiveFunction = self.subproblemSolutionForest.getTotalCost(
)
self.currentSolutionAssignment = self.subproblemSolutionForest.getAssignmentsArray(
)
initialQuantiles = copy.deepcopy(self.quantiles)
quantileSize = len(initialQuantiles)
quantilesCount = 0
customerCount = len(self.customers)
noImprovementIterations = 0
while True:
if (clock.isTimeOver(time.time(),
self.params["executionTimeLimit"])):
break
iterationsCount = len(self.clusterAreas)
for iteration in range(0, iterationsCount):
self.currentIteration = iteration
clustersCount = 0
clustersSize = len(self.clusterAreas.get(iteration))
for cluster in self.clusterAreas.get(iteration).values():
clustersCount = clustersCount + 1
print("Iteration: %s/%s || Instance: %s_%s" %
(quantilesCount + 1, quantileSize,
self.facilitiesCount, customerCount))
print("Subproblem: %s/%s" %
(self.currentIteration + 1, iterationsCount))
candidateForest = self.__destroy(cluster)
if (candidateForest.getTreesCount() *
candidateForest.getTotalNodes() >
self.MAX_PROBLEM_SIZE):
print(
"Problem instance is larger than limit. Skipping..."
)
candidateFacilities = [
tree.getRoot()
for tree in candidateForest.getTrees().values()
]
self.__updateFrequency(
dict([(facility.index, facility)
for facility in candidateFacilities]),
self.NO_ASSIGNMENT_REWARD)
continue
cFacilities, cCustomers = candidateForest.getData()
print(
"Current Cluster: %s/%s || Facilities: %s || Customers Assigned: %s"
% (clustersCount, clustersSize,
candidateForest.getTreesCount(),
candidateForest.getTotalNodes()))
if (candidateForest.getTotalNodes() == 0):
if (self.DEBUG_MESSAGES):
print("No Customers Assigned... Continue")
continue
obj, assignment, status = self.__repair(
cFacilities, cCustomers)
if (status == 'optimal'):
self.__evaluate(obj, assignment, candidateForest,
cluster)
else:
print("No Optimal Solution Found for this instance")
candidateFacilities = [
tree.getRoot()
for tree in candidateForest.getTrees().values()
]
self.__updateFrequency(
dict([(facility.index, facility)
for facility in candidateFacilities]),
self.ASSIGNMENT_REWARD)
print("Subproblem Forest: %s/%s" %
(self.subproblemSolutionForest.getTreesCount(),
self.subproblemSolutionForest.getTotalNodes()))
print("Subproblem Objective Funciton: %s" %
self.subproblemSolutionForest.getTotalCost())
print("Current Objective Function: %s" %
self.currentObjectiveFunction)
if (self.DEBUG_MESSAGES):
print("Partial Solution")
partial = ""
partial = '%.2f' % self.subproblemSolutionForest.getTotalCost(
) + ' ' + str(0) + '\n'
partial += ' '.join(
map(
str,
self.subproblemSolutionForest.getAssignmentsArray(
)))
print(partial)
if (self.currentObjectiveFunction >=
self.subproblemSolutionForest.getTotalCost()):
self.currentObjectiveFunction = self.subproblemSolutionForest.getTotalCost(
)
self.currentSolutionAssignment = self.subproblemSolutionForest.getAssignmentsArray(
)
else:
noImprovementIterations = noImprovementIterations + 1
print("====================================================")
print("CURRENT OBJECTIVE FUNCTION: %s" %
self.currentObjectiveFunction)
print("====================================================")
if (quantilesCount >= quantileSize):
print("Maximum Iteration Count Reached! Stopping...")
break
if (noImprovementIterations >
self.params["noImprovementIterationLimit"]):
print("No improvement limit reached! Stopping the search...")
break
##filtrar as facilities mais interessantes e jogar no facility subset
candidates = [
facility.index for facility in facilitySubet.values()
]
lastCandidateCount = len(candidates)
while quantilesCount < quantileSize and len(
candidates) == lastCandidateCount:
candidates = self.__getCandidateFacilities(
candidates, self.totalDemand,
Util.truncate(initialQuantiles[quantilesCount], 5), False)
quantilesCount = quantilesCount + 1
if (candidates is None or len(candidates) == 0
or len(candidates) == lastCandidateCount):
break
facilitySubet = dict(
zip([index for index in candidates],
[facilitySubet[index] for index in candidates]))
self.facilities = facilitySubet
self.__InitializeProblem(facilitySubet, customerSubset)
self.__getQuantiles()
return self.currentObjectiveFunction, self.currentSolutionAssignment
