def simulation_optimization_runV2(failureRates,
serviceRates,
holdingCosts,
penalty,
skillServerAssignment,
replications=replicationsDefault,
stopNrRequests=stopNrRequestsDefault,
numberWarmingUpRequests=0,
maxQ=maxQueue):
totalCostList = []
for i in xrange(replications):
numberInSystemDistributionAverage, _, _, _ = \
simulation_batch_run(failureRates = failureRates,
serviceRates = serviceRates,
skillServerAssignment = skillServerAssignment,
histogramBucketsInput = [],
expectedTotalNumberRequests = stopNrRequests,
numberWarmingUpRequests = numberWarmingUpRequests,
replications=1,
maxQueue=maxQ,
startSeed=100+i*30)
if numberInSystemDistributionAverage is not None:
totalCost, _, _ = OptimizeStockLevelsAndCostsSimBased(
holdingCosts, penalty, numberInSystemDistributionAverage)
totalCostList.append(totalCost)
return totalCostList
def simulation_optimization_run(failureRates,
serviceRates,
holdingCosts,
penalty,
skillServerAssignment,
stopNrRequests=stopNrRequestsDefault,
replications=replicationsDefault,
numberWarmingUpRequests=0,
runTheSimulation=True,
useDatabase=True,
maxQ=maxQueue):
numberInSystemDistributionAverage = None
utilizationRatesAverage = None
skillServerAssignmentStatisitcsAverage = None
m_skills = skillServerAssignment.shape[1]
n_servers = skillServerAssignment.shape[0]
databaseUpdated = False
if useDatabase:
numberInSystemDistributionAverage = getRecordFromDB(
n_servers, m_skills, failureRates, serviceRates,
skillServerAssignment)
if numberInSystemDistributionAverage is None and runTheSimulation:
# run the simulaiton
# print "run simulation:", skillServerAssignment, failureRates, serviceRates
if checkSkillAssignment(skillServerAssignment, failureRates,
serviceRates):
# print skillServerAssignment.tolist(), failureRates, serviceRates,
numberInSystemDistributionAverage, _, utilizationRatesAverage, skillServerAssignmentStatisitcsAverage\
= simulation_batch_run( failureRates = failureRates,
serviceRates = serviceRates,
skillServerAssignment = skillServerAssignment,
histogramBucketsInput = [],
# stopTimeInput=stopTime,
expectedTotalNumberRequests = stopNrRequests,
numberWarmingUpRequests = numberWarmingUpRequests,
replications=replications,
maxQueue=maxQ,
nCores=nCores)
if useDatabase:
databaseUpdated = writeToDB(
n_servers, m_skills, failureRates, serviceRates,
skillServerAssignment, numberInSystemDistributionAverage,
utilizationRatesAverage,
skillServerAssignmentStatisitcsAverage)
totalCost = float('inf')
S = np.zeros(m_skills, dtype=int)
EBO = np.zeros(m_skills)
if numberInSystemDistributionAverage is not None:
# print [np.nanmean([numberInSystemDistributionAverage[j][i-1]/numberInSystemDistributionAverage[j][i]*failureRates[j] for i in range(3,15)]) for j in range(m_skills)]
totalCost, S, EBO = OptimizeStockLevelsAndCostsSimBased(
holdingCosts, penalty, numberInSystemDistributionAverage)
return totalCost, S, EBO, databaseUpdated, utilizationRatesAverage, skillServerAssignmentStatisitcsAverage
print n, sku_num, failureRates, serviceRates,
assignmentID = 0
for skillServerAssignment in generateSkillsMultiServer(n, sku_num):
if checkSkillAssignment(skillServerAssignment, failureRates, serviceRates):
assignmentID +=1
case["assignments"][assignmentID] = dict()
case["assignments"][assignmentID]["skill_assignment"] = np.transpose(skillServerAssignment).tolist()
numberInSystemDistributionAverage, waitingTimeHistogramAverage, utilizationRatesAverage, skillServerAssignmentStatisitcsAverage \
= simulation_batch_run(failureRates, serviceRates, skillServerAssignment,
histogramBucketsInput = waitingTimeBuckets,
# stopTimeInput = stopTimeInput*np.sum(failureRates),
expectedTotalNumberRequests = stopNrRequests,
numberWarmingUpRequests = 1000,
replications=replications,
maxQueue=maxQueue,
nCores=cores)
case["assignments"][assignmentID]["queue_length_distributions"] = dict()
case["assignments"][assignmentID]["waiting_time_distributions"] = dict()
for sk in range(sku_num):
case["assignments"][assignmentID]["queue_length_distributions"][sk] \
= {k: v for k, v in zip(range(maxQueue), numberInSystemDistributionAverage[sk]) if v != 0} #remove zero values
case["assignments"][assignmentID]["waiting_time_distributions"][sk] \
= {k: v for k, v in zip(waitingTimeBuckets, waitingTimeHistogramAverage[sk]) if v != 0} #remove zero values
case["assignments"][assignmentID]["utilization_rates"] = utilizationRatesAverage.tolist()
case["assignments"][assignmentID]["skill_server_distribution"] = skillServerAssignmentStatisitcsAverage.tolist()
print assignmentID