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Commit ea65fe98 authored by Georgios Dagkakis's avatar Georgios Dagkakis
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progression to new LP

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dream/simulation/SkilledOperatorRouter.py
View file @ ea65fe98
......@@ -173,7 +173,7 @@ class SkilledRouter(Router):
#===================================================================
self.availableStationsDict={}
for station in self.availableStations:
self.availableStationsDict[str(station.id)]={'stationID':str(station.id),'WIP':station.wip}
self.availableStationsDict[str(station.id)]={'stationID':str(station.id),'WIP':station.wip, 'lastAssignment':self.env.now}
#===================================================================
# # operators and their skills set
#===================================================================
......
dream/simulation/opAss_LPmethod.py
View file @ ea65fe98
......@@ -4,7 +4,7 @@ Created on 2 Jul 2014
@author: Anna
'''
def opAss_LP(machineList, PBlist, PBskills, previousAssignment={}):
def opAss_LP(machineList, PBlist, PBskills, previousAssignment={}, weightFactors = [2, 1, 0.5, 2, 1, 1], Tool={}):
from pulp import LpProblem, LpMaximize, LpVariable, LpBinary, lpSum, LpStatus
import pulp
......@@ -14,129 +14,142 @@ def opAss_LP(machineList, PBlist, PBskills, previousAssignment={}):
machines = machineList.keys()
sumWIP = float(sum([machineList[mach]['WIP'] for mach in machines ]))
weightFactors = [2, 1, 0.5, 1.5]
# define LP problem
prob = LpProblem("PBassignment", LpMaximize)
obj = []
# declare variables...binary assignment variables (operator i to machine j)
PB_ass = LpVariable.dicts('PB', [(oper,mach) for oper in PBlist for mach in machines if machineList[mach]['stationID'] in PBskills[oper]] , 0, 1, cat=pulp.LpBinary)
# objective...assignment of PBs to stations with higher WIP...sum of WIP associated with stations where PB is assigned
obj = [machineList[mach]['WIP']*PB_ass[(oper,mach)]*weightFactors[0]/float(sumWIP) for oper in PBlist for mach in machines if machineList[mach]['stationID'] in PBskills[oper]]
if weightFactors[0]>0 and sumWIP>0:
obj.append([machineList[mach]['WIP']*PB_ass[(oper,mach)]*weightFactors[0]/float(sumWIP) for oper in PBlist for mach in machines if machineList[mach]['stationID'] in PBskills[oper]])
# second set of variables (delta assignment between stations) to facilitate the distribution of PBs across different stations
stationGroup = {}
for mach in machines:
if machineList[mach]['stationID'] not in stationGroup:
stationGroup[machineList[mach]['stationID']] = []
stationGroup[machineList[mach]['stationID']].append(mach)
Delta_Station = LpVariable.dicts("D_station",[(st1,st2) for i1, st1 in enumerate(stationGroup.keys()) for st2 in stationGroup.keys()[i1+1:]])
# calculate global max number of machines within a station that will be used as dividers for Delta_Station
maxNoMachines = 0
for st in stationGroup:
if len(stationGroup[st]) > maxNoMachines:
maxNoMachines = len(stationGroup[st])
# calculation of DeltaStation values
for i, st1 in enumerate(stationGroup.keys()):
tempList = []
for mach1 in stationGroup[st1]:
for oper1 in PBlist:
if st1 in PBskills[oper1]:
tempList.append(PB_ass[(oper1,mach1)]/float(maxNoMachines))
if weightFactors[1]>0:
stationGroup = {}
for mach in machines:
if machineList[mach]['stationID'] not in stationGroup:
stationGroup[machineList[mach]['stationID']] = []
stationGroup[machineList[mach]['stationID']].append(mach)
Delta_Station = LpVariable.dicts("D_station", [(st1, st2) for i1, st1 in enumerate(stationGroup.keys()) for st2 in stationGroup.keys()[i1 + 1:]])
# calculate global max number of machines within a station that will be used as dividers for Delta_Station
maxNoMachines = 0
for st in stationGroup:
if len(stationGroup[st]) > maxNoMachines:
maxNoMachines = len(stationGroup[st])
# calculation of DeltaStation values
for i, st1 in enumerate(stationGroup.keys()):
tempList = []
for mach1 in stationGroup[st1]:
for oper1 in PBlist:
if st1 in PBskills[oper1]:
tempList.append(PB_ass[(oper1,mach1)]/float(maxNoMachines))
for st2 in stationGroup.keys()[i+1:]:
for st2 in stationGroup.keys()[i+1:]:
finalList = copy.copy(tempList)
for mach2 in stationGroup[st2]:
for oper2 in PBlist:
if st2 in PBskills[oper2]:
finalList.append(PB_ass[(oper2,mach2)]*-1/float(maxNoMachines))
finalList = copy.copy(tempList)
for mach2 in stationGroup[st2]:
for oper2 in PBlist:
if st2 in PBskills[oper2]:
finalList.append(PB_ass[(oper2,mach2)]*-1/float(maxNoMachines))
prob += lpSum(finalList)>= Delta_Station[(st1,st2)]
prob += lpSum([i*-1 for i in finalList])>= Delta_Station[(st1,st2)]
prob += lpSum(finalList)>= Delta_Station[(st1,st2)]
prob += lpSum([i*-1 for i in finalList])>= Delta_Station[(st1,st2)]
# integration of second obj
normalisingFactorDeltaStation = 0
for i in range(len(stationGroup)):
normalisingFactorDeltaStation += i
for i1, st1 in enumerate(stationGroup.keys()):
for st2 in stationGroup.keys()[i1+1:]:
obj.append(Delta_Station[(st1,st2)]*weightFactors[1]/float(normalisingFactorDeltaStation) )
# integration of second obj
normalisingFactorDeltaStation = 0
for i in range(len(stationGroup)):
normalisingFactorDeltaStation += i
for i1, st1 in enumerate(stationGroup.keys()):
for st2 in stationGroup.keys()[i1+1:]:
obj.append(Delta_Station[(st1,st2)]*weightFactors[1]/float(normalisingFactorDeltaStation) )
# min variation in PB assignment
Delta_Assignment = []
OldAss = {}
for pb in previousAssignment:
if pb in PBlist:
for station in PBskills[pb]:
for mach in machineList:
if machineList[mach]['stationID'] == station:
Delta_Assignment.append([pb, mach])
if previousAssignment[pb] == mach:
OldAss[(pb,mach)] = 1
else:
OldAss[(pb,mach)] = 0
if weightFactors[2]>0:
Delta_Assignment = []
OldAss = {}
for pb in previousAssignment:
if pb in PBlist:
for station in PBskills[pb]:
for mach in machineList:
if machineList[mach]['stationID'] == station:
Delta_Assignment.append([pb, mach])
if previousAssignment[pb] == mach:
OldAss[(pb,mach)] = 1
else:
OldAss[(pb,mach)] = 0
# create delta assignment variables
Delta_Ass = LpVariable.dicts("D_Ass",[(d[0],d[1]) for d in Delta_Assignment])
# create delta assignment variables
Delta_Ass = LpVariable.dicts("D_Ass",[(d[0],d[1]) for d in Delta_Assignment])
# integration of third objective
for d in Delta_Assignment:
obj.append(Delta_Ass[(d[0], d[1])]*(-1.0*weightFactors[2]/(2*len(previousAssignment))) )
# integration of third objective
for d in Delta_Assignment:
obj.append(Delta_Ass[(d[0], d[1])]*(-1.0*weightFactors[2]/(2*len(previousAssignment))) )
# calculation of Delta_Ass
for d in Delta_Assignment:
if OldAss[(d[0],d[1])] == 1:
prob += lpSum(OldAss[(d[0],d[1])] - PB_ass[(d[0],d[1])]) <= Delta_Ass[(d[0],d[1])]
else:
prob += lpSum(PB_ass[(d[0],d[1])] - OldAss[(d[0],d[1])]) <= Delta_Ass[(d[0],d[1])]
# calculation of Delta_Ass
for d in Delta_Assignment:
if OldAss[(d[0],d[1])] == 1:
prob += lpSum(OldAss[(d[0],d[1])] - PB_ass[(d[0],d[1])]) <= Delta_Ass[(d[0],d[1])]
else:
prob += lpSum(PB_ass[(d[0],d[1])] - OldAss[(d[0],d[1])]) <= Delta_Ass[(d[0],d[1])]
# 4th obj = fill a subline
# verify whether there are machines active in the sublines
subline={0:{'noMach':0, 'WIP':0}, 1:{'noMach':0, 'WIP':0}}
for mach in machineList:
if machineList[mach]['stationID'] in [0,1,2]:
subline[machineList[mach]['machineID']]['noMach'] += 1
subline[machineList[mach]['machineID']]['WIP'] += machineList[mach]['WIP']
chosenSubLine = False
# choose subline to be filled first
if subline[0]['noMach'] == 3:
# case when both sublines are fully active
if subline[1]['noMach'] == 3:
if subline[0]['WIP'] >= subline [1]['WIP']:
chosenSubLine = 1
if weightFactors[3]>0:
# verify whether there are machines active in the sublines
subline={0:{'noMach':0, 'WIP':0}, 1:{'noMach':0, 'WIP':0}}
for mach in machineList:
if machineList[mach]['stationID'] in [0,1,2]:
subline[machineList[mach]['machineID']]['noMach'] += 1
subline[machineList[mach]['machineID']]['WIP'] += machineList[mach]['WIP']
chosenSubLine = False
# choose subline to be filled first
if subline[0]['noMach'] == 3:
# case when both sublines are fully active
if subline[1]['noMach'] == 3:
if subline[0]['WIP'] >= subline [1]['WIP']:
chosenSubLine = 1
else:
chosenSubLine = 2
else:
chosenSubLine = 2
else:
chosenSubLine = 1
elif subline[1]['noMach'] == 3:
chosenSubLine = 2
#create variable for the chosen subline
if chosenSubLine:
chosenSubLine -= 1
subLine = LpVariable('SubL', lowBound=0)
sub = []
for station in range(3):
mach = G.Tool[station][chosenSubLine].name #'St'+str(station)+'_M'+str(chosenSubLine)
for oper in PBlist:
if station in PBskills[oper]:
sub.append(PB_ass[(oper,mach)])
chosenSubLine = 1
elif subline[1]['noMach'] == 3:
chosenSubLine = 2
#create variable for the chosen subline
if chosenSubLine:
chosenSubLine -= 1
subLine = LpVariable('SubL', lowBound=0)
sub = []
for station in range(3):
mach = Tool[station][chosenSubLine].name #'St'+str(station)+'_M'+str(chosenSubLine)
for oper in PBlist:
if station in PBskills[oper]:
sub.append(PB_ass[(oper,mach)])
prob += lpSum(sub) >= subLine
chosenSubLine+=1
obj.append(subLine*weightFactors[3]/3.0)
prob += lpSum(sub) >= subLine
chosenSubLine+=1
obj.append(subLine*weightFactors[3]/3.0)
# 5th objective: prioritise machines with furthest in time last assignment
LastAssignmentSum = float(sum([machineList[mach]['lastAssignment'] for mach in machines ]))
if LastAssignmentSum > 0 and weightFactors[4]>0:
obj += [machineList[mach]['lastAssignment']*PB_ass[(oper,mach)]*weightFactors[4]/float(LastAssignmentSum) for oper in PBlist for mach in machines if machineList[mach]['stationID'] in PBskills[oper]]
# 6th objective: max the number of pb assigned
if weightFactors[5]>0:
obj += [PB_ass[(oper,mach)]*weightFactors[5]/float(len(PBlist)) for oper in PBlist for mach in machines if machineList[mach]['stationID'] in PBskills[oper]]
prob += lpSum(obj)
......@@ -147,7 +160,11 @@ def opAss_LP(machineList, PBlist, PBskills, previousAssignment={}):
# constraint 2: # machines assigned to an operator <= 1
for operator in PBlist:
prob += lpSum([PB_ass[(operator,machine)] for machine in machines if machineList[machine]['stationID'] in PBskills[operator]]) <= 1
# write the problem data to an .lp file.
prob.writeLP("PBassignment.lp")
prob.solve()
if LpStatus[prob.status] != 'Optimal':
......@@ -160,7 +177,7 @@ def opAss_LP(machineList, PBlist, PBskills, previousAssignment={}):
if machineList[mach]['stationID'] in PBskills[oper]:
if PB_ass[(oper,mach)].varValue > 0.00001:
PBallocation[oper]=mach
files = glob.glob('*.mps')
for f in files:
os.remove(f)
......@@ -170,7 +187,6 @@ def opAss_LP(machineList, PBlist, PBskills, previousAssignment={}):
os.remove(f)
return PBallocation
\ No newline at end of file
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