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Commit 1fcc8ffa authored by Georgios Dagkakis's avatar Georgios Dagkakis
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changes in the algorithm copied

parent 83f69770
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Showing with 153 additions and 60 deletions
dream/plugins/DemandPlanning/DemandPlanningLine.py
View file @ 1fcc8ffa
......@@ -34,8 +34,13 @@ class DemandPlanningLine(plugin.OutputPreparationPlugin, TimeSupportMixin):
options = {
"xaxis": {
"mode": "time",
"minTickSize": [1, self.getTimeUnitText()],
}
#"minTickSize": [1, self.getTimeUnitText()],
"minTickSize": [1, "day"],
},
"legend": {
"backgroundOpacity": 0.1,
"position":"se",
},
}
bottleNeckUtilizationDict[bottleneck] = {
......@@ -84,13 +89,18 @@ class BottleNeckByWeek(plugin.OutputPreparationPlugin, TimeSupportMixin):
for week, bottleneckData in by_week.items():
series = []
ticks = list(enumerate(bottleneckData.keys()))
#ticks = list(enumerate(bottleneckData.keys()))
ticks = list(enumerate(G.Bottlenecks))
options = {
"xaxis": {
"minTickSize": 1,
"ticks": ticks
},
"legend": {
"backgroundOpacity": 0.1,
"position":"se",
},
"series": {
"bars": {
"show": True,
......@@ -115,7 +125,7 @@ class BottleNeckByWeek(plugin.OutputPreparationPlugin, TimeSupportMixin):
( 'maxUtilization', 'Target Utilization' ) ]:
series.append({
"label": utilizationLabel,
"data": list(enumerate([x[utilizationType] for x in bottleneckData.values()])),
"data": list(enumerate([bottleneckData[x][utilizationType] for x in G.Bottlenecks])),
})
return data
\ No newline at end of file
dream/simulation/applications/DemandPlanning/AllocationRoutine_Final2.py
View file @ 1fcc8ffa
......@@ -150,9 +150,9 @@ def AllocationRoutine_Final(initialWeek, itemList, itemType, ant):
# for orders add allocation information
if itemType == 'order':
if chosenMA == None:
G.OrderResults.append((item['orderID'], item['sp'], item['MAlist'], item['Week'], item['Customer'], item['Qty'], item['priority'], chosenMA, oMAlist2, 'NaN', 'NaN', 'None'))
G.OrderResults.append((item['orderID'], item['sp'], item['MAlist'], item['Week'], item['Qty'], item['priority'], chosenMA, oMAlist2, 'NaN', 'NaN', 'None'))
else:
G.OrderResults.append((item['orderID'], item['sp'], item['MAlist'], item['Week'], item['Customer'], item['Qty'], item['priority'], chosenMA, oMAlist2, Results[chosenMA]['lateness'], Results[chosenMA]['earliness'], Results[chosenMA]['Allocation']))
G.OrderResults.append((item['orderID'], item['sp'], item['MAlist'], item['Week'], item['Qty'], item['priority'], chosenMA, oMAlist2, Results[chosenMA]['lateness'], Results[chosenMA]['earliness'], Results[chosenMA]['Allocation']))
if itemType == 'forecast':
if chosenMA == None:
......@@ -180,8 +180,15 @@ def choseMA(allResults, possibleSolutions, MAlist, weeklist):
for week in weeklist:
for bn in allResults[ma]['utilisation']:
if week in allResults[ma]['utilisation'][bn]:
if G.Capacity[bn][week]['minUtilisation']:
minUtil.append(max(0, (G.Capacity[bn][week]['minUtilisation']-allResults[ma]['utilisation'][bn][week])/G.Capacity[bn][week]['minUtilisation']))
else:
minUtil.append(max(0, (G.Capacity[bn][week]['minUtilisation']-allResults[ma]['utilisation'][bn][week])))
if G.Capacity[bn][week]['targetUtilisation']:
targetUtil.append((G.Capacity[bn][week]['targetUtilisation']-allResults[ma]['utilisation'][bn][week])/G.Capacity[bn][week]['targetUtilisation'])
else:
targetUtil.append(G.Capacity[bn][week]['targetUtilisation']-allResults[ma]['utilisation'][bn][week])
res.append([ma, allResults[ma]['remainingUnits'], allResults[ma]['lateness'], std(array(targetUtil)), std(array(minUtil)), allResults[ma]['earliness']])
......@@ -218,13 +225,20 @@ def choseMA2(allResults, possibleSolutions, MAlist, weeklist): # more simil
targetU = []
for week in weeklist:
utilisation = float(G.Capacity[bottleneck][week]['OriginalCapacity'] - allResults[ma]['remainingCap'][bottleneck][week])/G.Capacity[bottleneck][week]['OriginalCapacity']
if G.Capacity[bottleneck][week]['minUtilisation']:
minU.append(max(0, (G.Capacity[bottleneck][week]['minUtilisation']-utilisation)/G.Capacity[bottleneck][week]['minUtilisation']))
else:
minU.append(max(0, (G.Capacity[bottleneck][week]['minUtilisation']-utilisation)))
if G.Capacity[bottleneck][week]['targetUtilisation']:
targetU.append((utilisation - G.Capacity[bottleneck][week]['targetUtilisation'])/G.Capacity[bottleneck][week]['targetUtilisation'])
else:
targetU.append((utilisation - G.Capacity[bottleneck][week]['targetUtilisation']))
minUtil.append(mean(array(minU)))
targetUtil.append(mean(absolute(targetU)))
res.append([ma, allResults[ma]['remainingUnits'], allResults[ma]['lateness'], std(array(targetUtil)), std(array(minUtil)), allResults[ma]['earliness']])
res.append([ma, allResults[ma]['remainingUnits'], allResults[ma]['lateness'], mean(array(targetUtil)), mean(array(minUtil)), allResults[ma]['earliness']])
# order results...1st criterion: target utilisation (stdDev), 2nd criterion: min utilisation(stdDev)
sortedMA = sorted(res, key=itemgetter(1, 2, 3, 4, 5))
......
dream/simulation/applications/DemandPlanning/Globals.py
View file @ 1fcc8ffa
......@@ -80,7 +80,7 @@ class G:
# output variables
reportResults = tablib.Databook()
OrderResults = tablib.Dataset(title='OrderSummary')
OrderResults.headers = ('OrderID', 'SP_NUMBER', 'MA_LIST', 'REQUEST_DATE', 'DFSELLER', 'ORDERQTY', 'PRIORITY', 'CHOSEN_MA','ORDERED_MA_LIST', 'LATENESS', 'EARLINESS', 'ALLOCATION')
OrderResults.headers = ('OrderID', 'SP_NUMBER', 'MA_LIST', 'REQUEST_DATE', 'ORDERQTY', 'PRIORITY', 'CHOSEN_MA','ORDERED_MA_LIST', 'LATENESS', 'EARLINESS', 'ALLOCATION')
forecastResults = tablib.Dataset(title='ForecastSummary')
forecastResults.headers = ('PPOS', 'SP_NUMBER', 'MA_LIST', 'REQUEST_DATE', 'ORDERQTY', 'PRIORITY', 'CHOSEN_MA', 'LATENESS', 'EARLINESS', 'ALLOCATION')
globalMAAllocation = {}
......@@ -150,7 +150,7 @@ def initialiseVar():
# output variables
G.reportResults = tablib.Databook()
G.OrderResults = tablib.Dataset(title='OrderSummary')
G.OrderResults.headers = ('OrderID', 'SP_NUMBER', 'MA_LIST', 'REQUEST_DATE', 'DFSELLER', 'ORDERQTY', 'PRIORITY', 'CHOSEN_MA','ORDERED_MA_LIST', 'LATENESS', 'EARLINESS', 'ALLOCATION')
G.OrderResults.headers = ('OrderID', 'SP_NUMBER', 'MA_LIST', 'REQUEST_DATE', 'ORDERQTY', 'PRIORITY', 'CHOSEN_MA','ORDERED_MA_LIST', 'LATENESS', 'EARLINESS', 'ALLOCATION')
G.forecastResults = tablib.Dataset(title='ForecastSummary')
G.forecastResults.headers = ('PPOS', 'SP_NUMBER', 'MA_LIST', 'REQUEST_DATE', 'ORDERQTY', 'PRIORITY', 'CHOSEN_MA', 'LATENESS', 'EARLINESS', 'ALLOCATION')
G.CapacityResults = None
......
dream/simulation/applications/DemandPlanning/ImportInput.py
View file @ 1fcc8ffa
......@@ -50,6 +50,7 @@ def ImportInput(input, algorithmAttributes):
wbin = xlrd.open_workbook(file_contents=attachement_data)
G.maxEarliness = algorithmAttributes.get('maxEarliness',None)
G.maxLateness = algorithmAttributes.get('maxLateness',None)
startWeek = algorithmAttributes.get('CurrentWeek',None)
# utilisation calculation
G.minDeltaUt = algorithmAttributes.get('minDelta',None)
......@@ -81,12 +82,24 @@ def ImportInput(input, algorithmAttributes):
sh = wbin.sheet_by_name('BN_Capa')
rows = sh.nrows
G.planningHorizon = sh.ncols - 2
Weeks = {}
for week in range(2,sh.ncols):
w = 2
while w<sh.ncols and withoutFormat(1,w,sh,1) != startWeek:
w += 1
if w == sh.ncols:
print "please enter a valid week value"
return "stop"
refCap = {}
noTarget = []
for week in range(w,sh.ncols):
Weeks[week] = withoutFormat(1,week,sh,1)
G.WeekList.append(withoutFormat(1,week,sh,1))
refCap[Weeks[week]] = 1
G.planningHorizon = len(G.WeekList)
for row in range(2,rows,4):
bn = withoutFormat(row,0,sh,0)
......@@ -95,18 +108,42 @@ def ImportInput(input, algorithmAttributes):
G.Capacity[bn] = {}#{'OriginalCapacity':{}, 'RemainingCapacity':{}, 'minUtilisation':{}, 'targetUtilisation':{}}
G.CurrentCapacityDictOrig[bn] = {}
for week in range(2,sh.ncols):
G.Capacity[bn][Weeks[week]]={'OriginalCapacity':withoutFormat(row,week,sh,1), 'RemainingCapacity':withoutFormat(row+1,week,sh,1), 'minUtilisation':withoutFormat(row+2,week,sh,0), 'targetUtilisation':withoutFormat(row+3,week,sh,0)}
for week in range(w,sh.ncols):
G.Capacity[bn][Weeks[week]]={'OriginalCapacity':withoutFormat(row,week,sh,1), 'RemainingCapacity':withoutFormat(row+1,week,sh,1), 'minUtOrig':withoutFormat(row+2,week,sh,0), 'targetUtOrig':withoutFormat(row+3,week,sh,0)}
if G.Capacity[bn][Weeks[week]]['minUtOrig'] == '':
G.Capacity[bn][Weeks[week]]['minUtilisation'] = 0
else:
G.Capacity[bn][Weeks[week]]['minUtilisation'] = G.Capacity[bn][Weeks[week]]['minUtOrig']
if G.Capacity[bn][Weeks[week]]['targetUtOrig'] == '':
G.Capacity[bn][Weeks[week]]['targetUtilisation'] = 1
noTarget.append([bn, Weeks[week]])
else:
G.Capacity[bn][Weeks[week]]['targetUtilisation'] = G.Capacity[bn][Weeks[week]]['targetUtOrig']
if G.Capacity[bn][Weeks[week]]['targetUtOrig'] < refCap[Weeks[week]]:
refCap[Weeks[week]] = G.Capacity[bn][Weeks[week]]['targetUtOrig']
G.CurrentCapacityDictOrig[bn][Weeks[week]] = withoutFormat(row,week,sh,1)
for coppie in noTarget:
if refCap[coppie[1]] == 1:
refCap[coppie[1]] = 0
G.Capacity[coppie[0]][coppie[1]]['targetUtilisation'] = refCap[coppie[1]]
# Import loading factors
sh = wbin.sheet_by_name('BN_Load Factor')
rows = sh.nrows
w = 3
while withoutFormat(1,w,sh,1) != startWeek:
w += 1
Weeks = {}
for week in range(3,sh.ncols):
for week in range(w,sh.ncols):
Weeks[week] = withoutFormat(1,week,sh,1)
for row in range(2,rows):
......@@ -125,15 +162,19 @@ def ImportInput(input, algorithmAttributes):
bn = withoutFormat(row,2,sh,0)
G.RouteDict[ma][bn] = {}
for week in range(3,sh.ncols):
for week in range(w,sh.ncols):
G.RouteDict[ma][bn][Weeks[week]] = withoutFormat(row,week,sh,0)
# Import batch size
sh = wbin.sheet_by_name('BatchSize')
rows = sh.nrows
w = 2
while withoutFormat(2,w,sh,1) != startWeek:
w += 1
Weeks = {}
for week in range(2,sh.ncols):
for week in range(w,sh.ncols):
Weeks[week] = withoutFormat(2,week,sh,1)
for row in range(3,rows):
......@@ -144,7 +185,7 @@ def ImportInput(input, algorithmAttributes):
G.BatchSize[ma]= {}
G.incompleteBatches[ma] = 0
for week in range(2,sh.ncols):
for week in range(w,sh.ncols):
G.BatchSize[ma][Weeks[week]] = withoutFormat(row,week,sh,0)
# G.incompleteBatches[ma][Weeks[week]] = 0
......@@ -153,24 +194,28 @@ def ImportInput(input, algorithmAttributes):
sh = wbin.sheet_by_name('OrderSummary')
rows = sh.nrows
orderID = 1
G.priorityList['order'] = []
G.sortedOrders['order'] = {}
for row in range(1,rows):
week = withoutFormat(row,3,sh,1)
if week < startWeek:
continue
orderID = withoutFormat(row,2,sh,0)
G.orders[orderID] = {}
G.orders[orderID]['orderID'] = orderID
G.orders[orderID]['ppos'] = 0
G.orders[orderID]['sp'] = withoutFormat(row,1,sh,0)
maList = withoutFormat(row,2,sh,0)
G.orders[orderID]['sp'] = withoutFormat(row,0,sh,0)
maList = withoutFormat(row,1,sh,0)
maList = my_split(maList, ['; ', ';'])
print 'malist', maList
maList.remove('')
G.orders[orderID]['MAlist'] = maList
week = withoutFormat(row,3,sh,1)
G.orders[orderID]['Week'] = week
G.orders[orderID]['Customer'] = withoutFormat(row, 4, sh, 0)
G.orders[orderID]['Qty'] = withoutFormat(row, 5, sh, 0)
priority = withoutFormat(row, 6, sh, 1)
G.orders[orderID]['Qty'] = withoutFormat(row, 4, sh, 0)
priority = withoutFormat(row, 5, sh, 1)
G.orders[orderID]['priority'] = priority
if priority not in G.priorityList['order']:
G.priorityList['order'].append(priority)
......@@ -179,19 +224,22 @@ def ImportInput(input, algorithmAttributes):
if week not in G.sortedOrders['order'][priority]:
G.sortedOrders['order'][priority][week] = []
G.sortedOrders['order'][priority][week].append(G.orders[orderID])
orderID += 1
print 'sorted orders keys', G.sortedOrders['order'].keys()
# Import forecast
sh = wbin.sheet_by_name('FC_Summary')
rows = sh.nrows
G.priorityList['forecast'] = []
G.sortedOrders['forecast'] = {}
Weeks = {}
w = 3
while withoutFormat(1,w,sh,1) != startWeek:
w += 1
for week in range(3,sh.ncols):
Weeks[week] = withoutFormat(1,week,sh,1)
row = 2
row = w
while row < rows:
newSp = withoutFormat(row,1,sh,0)
......@@ -210,6 +258,8 @@ def ImportInput(input, algorithmAttributes):
subRow += 1
print 'ma sug', maSuggested, subRow
oID = 1
orderID = 'Forecast_'+str(oID)
for week in range(4,sh.ncols):
qty = withoutFormat(row+subRow,week,sh,1)
if qty:
......@@ -233,7 +283,8 @@ def ImportInput(input, algorithmAttributes):
if Weeks[week] not in G.sortedOrders['forecast'][priority]:
G.sortedOrders['forecast'][priority][Weeks[week]] = []
G.sortedOrders['forecast'][priority][Weeks[week]].append(G.orders[orderID])
orderID += 1
oID += 1
orderID = 'Forecast_'+str(oID)
row += subRow+1
......@@ -282,3 +333,4 @@ def ImportInput(input, algorithmAttributes):
if __name__ == '__main__':
ImportInput()
\ No newline at end of file
dream/simulation/applications/DemandPlanning/UtilisationCalculation.py
View file @ 1fcc8ffa
......@@ -51,12 +51,15 @@ def utilisationCalc1(ACOcapacityDict, initialWeek, ind):
for week in weekList:
utilisation = float(G.Capacity[bottleneck][week]['OriginalCapacity']-ACOcapacityDict[bottleneck][week])/G.Capacity[bottleneck][week]['OriginalCapacity']
minU.append(utilisation > G.Capacity[bottleneck][week]['minUtilisation'])
if G.Capacity[bottleneck][week]['targetUtilisation']:
targetU.append(float(utilisation - G.Capacity[bottleneck][week]['targetUtilisation'])/G.Capacity[bottleneck][week]['targetUtilisation'])
else:
targetU.append(float(utilisation - G.Capacity[bottleneck][week]['targetUtilisation']))
minUtil.append(mean(array(minU)))
targetUtil.append(mean(absolute(targetU)))
ACOtargetUtil = std(array(targetUtil)) #mean(array(targetUtil)) #FIXME: potrebbe essere std(array(targetUtil))
ACOtargetUtil = mean(array(targetUtil)) #mean(array(targetUtil)) #FIXME: potrebbe essere std(array(targetUtil))
ACOminUtil = mean(array(minUtil))*-1
return ACOtargetUtil, ACOminUtil
......@@ -72,11 +75,14 @@ def utilisationCalc2(ACOcapacityDict, initialWeek, ind):
minUtil = []
targetUtil = []
for bottleneck in G.Bottlenecks:
weekList = [initialWeek] + [G.WeekList[i] for i in range(ind-1, max(-1,ind-G.maxEarliness-1), -1)]
weekList = [initialWeek] #+ [G.WeekList[i] for i in range(ind-1, max(-1,ind-G.maxEarliness-1), -1)]
for week in weekList:
utilisation = float(G.Capacity[bottleneck][week]['OriginalCapacity']-ACOcapacityDict[bottleneck][week])/G.Capacity[bottleneck][week]['OriginalCapacity']
minUtil.append(utilisation > G.Capacity[bottleneck][week]['minUtilisation'])
if G.Capacity[bottleneck][week]['targetUtilisation']:
targetUtil.append(float(utilisation - G.Capacity[bottleneck][week]['targetUtilisation'])/G.Capacity[bottleneck][week]['targetUtilisation'])
else:
targetUtil.append(float(utilisation - G.Capacity[bottleneck][week]['targetUtilisation']))
ACOtargetUtil = std(array(targetUtil))
ACOminUtil = mean(array(minUtil))*-1
......@@ -100,7 +106,10 @@ def utilisationCalc3(ACOcapacityDict, initialWeek, ind):
for week in weekList:
utilisation = float(G.Capacity[bottleneck][week]['OriginalCapacity']-ACOcapacityDict[bottleneck][week])/G.Capacity[bottleneck][week]['OriginalCapacity']
minU.append(utilisation)
if G.Capacity[bottleneck][week]['targetUtilisation']:
targetU.append(float(utilisation - G.Capacity[bottleneck][week]['targetUtilisation'])/G.Capacity[bottleneck][week]['targetUtilisation'])
else:
targetU.append(float(utilisation - G.Capacity[bottleneck][week]['targetUtilisation']))
minUtil.append(mean(array(minU)))
targetUtil.append(mean(array(max(minU))))
......
dream/simulation/applications/DemandPlanning/executor_M_controlled.py
View file @ 1fcc8ffa
......@@ -29,22 +29,27 @@ from ImportInput import ImportInput
from outputResults import outputResults
from Globals import G, initialiseVar
import time
from numpy import mean, std, array
from numpy import mean, std, array, absolute
from operator import itemgetter
def main(input, algorithmAttributes):
startTime = time.time()
ImportInput(input, algorithmAttributes)
if str(G.ACO).lower() == "all":
ver = ImportInput(input, algorithmAttributes)
if ver == "stop":
return
if G.ACO == "all":
G.acoRange = [0,1]
G.minRange = {0:[0,1],1:[0,1]}
elif str(G.ACO) == "1":
G.acoRange = [0,1]
G.minRange = {0:[0,1],1:[G.minDeltaUt]}
elif G.ACO == "1":
G.acoRange = [1]
G.minRange = {0:[0,1], 1:[G.minDeltaUt]}
else:
G.acoRange = [0]
G.minRange = {0:[G.minDeltaUt]}
for j in G.acoRange:
for i in G.minRange[j]:
initialiseVar()
......@@ -68,9 +73,12 @@ def main(input, algorithmAttributes):
for bottleneck in G.Bottlenecks:
for week in G.WeekList:
utilisation.append(float(G.Capacity[bottleneck][week]['OriginalCapacity']-G.CurrentCapacityDict[bottleneck][week])/G.Capacity[bottleneck][week]['OriginalCapacity'])
if G.Capacity[bottleneck][week]['targetUtilisation']:
targetUt.append((G.Capacity[bottleneck][week]['targetUtilisation']-float(G.Capacity[bottleneck][week]['OriginalCapacity']-G.CurrentCapacityDict[bottleneck][week])/G.Capacity[bottleneck][week]['OriginalCapacity'])/G.Capacity[bottleneck][week]['targetUtilisation'])
else:
targetUt.append((G.Capacity[bottleneck][week]['targetUtilisation']-float(G.Capacity[bottleneck][week]['OriginalCapacity']-G.CurrentCapacityDict[bottleneck][week])/G.Capacity[bottleneck][week]['OriginalCapacity']))
G.Summary[(G.ACO,G.minDeltaUt)]['utilisation'] = mean(array(utilisation))
G.Summary[(G.ACO,G.minDeltaUt)]['targetM'] = mean(array(targetUt))
G.Summary[(G.ACO,G.minDeltaUt)]['targetM'] = mean(absolute(array(targetUt)))
G.Summary[(G.ACO,G.minDeltaUt)]['targetStd'] = std(array(targetUt))
if G.ACO:
G.Summary[(G.ACO,G.minDeltaUt)]['ant'] = bestAnt
......@@ -81,7 +89,7 @@ def main(input, algorithmAttributes):
# selection
listSummary = [G.Summary[item] for item in G.Summary.keys()]
print 'list summary', listSummary
listSummary = sorted(listSummary, key=itemgetter('exUnits', 'lateness', 'targetStd', 'utilisation','targetM', 'earliness'))
listSummary = sorted(listSummary, key=itemgetter('exUnits', 'lateness', 'targetM', 'targetStd', 'utilisation', 'earliness'))
bestScenario = listSummary[0]['scenario']
aco = bestScenario[0]
......
dream/simulation/applications/DemandPlanning/outputResults.py
View file @ 1fcc8ffa
......@@ -71,7 +71,7 @@ def outputResults():
G.CapacityResults.append([bottleneck, 'Capa Pegging Resource Capacity (UoM)',]+initialCap)
G.CapacityResults.append(['', 'Capa Pegging Resource Total Load (UoM)',]+[G.Capacity[bottleneck][week]['OriginalCapacity']-G.CurrentCapacityDict[bottleneck][week] for week in G.WeekList])
G.CapacityResults.append(['', 'Capa Pegging Resource Total Util (Percent)',]+[float(G.Capacity[bottleneck][week]['OriginalCapacity']-G.CurrentCapacityDict[bottleneck][week])/G.Capacity[bottleneck][week]['OriginalCapacity']*100 for week in G.WeekList])
G.CapacityResults.append(['', 'Capa Pegging Resource Min Util (Percent)',]+[G.Capacity[bottleneck][week]['minUtilisation']*100 for week in G.WeekList])
G.CapacityResults.append(['', 'Capa Pegging Resource Min Util (Percent)',]+[G.Capacity[bottleneck][week]['minUtOrig']*100 for week in G.WeekList])
G.CapacityResults.append(['', 'Capa Pegging Resource Target Util (Percent)',]+[G.Capacity[bottleneck][week]['targetUtilisation']*100 for week in G.WeekList])
# utilisation results
......
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