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mixed_fleet_deployment.py
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mixed_fleet_deployment.py
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'''
Author: Tanveer Hossain Bhuiyan, Ph.D. Contact: tanveer.bhuiyan@utsa.edu
Assistant Professor, The University of Texas at San Antonio. This code implements the mixed drone ground vehicle fleet routing
'''
import pandas as pd
import math
from math import sin, cos, sqrt, atan2, radians
from machineLearningModel import ascend, descend, hover, forwardFlight
import requests
import json
# import itertools
from datetime import datetime, timedelta
from docplex.mp.model import Model
import time
import itertools
# Data initialization
providerLocation = "ProviderLocationScenario_1.csv"
droneData = "DroneDataScenario_1.csv"
deliveryData = "Input_data.csv"
OnlyDrone = False
minNumberOfDrones = True
debug = True
batteryReplacement = True
visualization = False
packageDropping = False
gap = 0.15
hoveringBolLoaded = True
hoveringBolUnloaded = True
maxPermissibleDelay = 1200.0
packageUnloadingTimeDropping = 30.0
if packageDropping == True:
packageUnloadingTimeLanding = 0.0
else:
packageUnloadingTimeLanding = 30.0
packageLoadingTime = 300.0
packageLoadingTimeVehicle = 300
packageUnloadingTimeVehicle = 120
air_density = 1.2754
t_0 = datetime.strptime('2/3/2015 1:00', "%m/%d/%Y %H:%M").timestamp()
droneType = 'Small VTOL'
C_L = 60.0
n_d = 5.0
C_L_d = math.ceil(C_L/n_d)
C_E = 0.13
vehicle = 'Hyundai Accent 2022'
if vehicle == 'Toyota Prius 2021':
C_v = 0.0064
C_mv = 0.22
C_lv = 16.83
MPG = 54
elif vehicle == 'KIA Niro 2022':
C_v = 0.0062
C_mv = 0.25
C_lv = 16.83
MPG = 51
elif vehicle == 'Honda Insight 2022':
C_v = 0.00644
C_mv = 0.22
C_lv = 16.83
MPG = 55
elif vehicle == 'Hyundai Accent 2022':
C_v = 0.0049
C_mv = 0.25
C_lv = 16.83
MPG = 33
else:
C_v = 0.00501
C_mv = 0.22
C_lv = 16.83
MPG = 31
conversionFactor = 33.7
vehicleEnergyConsumptionPerMile = conversionFactor / MPG
M = 10000.0
gta = 0.2
grvitational_constant = 9.81
whTokwhConvert = 0.001
wsecToWattHourConvert = 1/3600
hourToSecConvert = 3600.0
AscendHeight = 200
durationAscendLoaded = 25.002
avgWattAngleAscendLoaded = 0.0
durationAngleAscendLoaded = 0.0
if packageDropping == True:
durationDescendLoaded = 35.209
else:
durationDescendLoaded = 45.209
avgWattAngleDescendLoaded = 0.0
durationAngleDescendLoaded = 0.0
if hoveringBolLoaded == True:
if packageDropping == True:
durationHoverLoaded = 30.0
else:
durationHoverLoaded = 5.0
if packageDropping == True:
durationAscendUnloaded = 20.002
else:
durationAscendUnloaded = 25.002
avgWattAngleAscendUnloaded = 0.0
durationAngleAscendUnloaded = 0.0
durationDescendUnloaded = 45.209
avgWattAngleDescendUnloaded = 0.0
durationAngleDescendUnloaded = 0.0
if hoveringBolUnloaded == True:
avgWattHoverUnloaded = 1039.254162
durationHoverUnloaded = 5.0
class Node:
def __init__(self, deliveryID, readyTime, lat, lon, payload):
self.deliveryID = deliveryID
self.readyTime = readyTime
self.lat = lat
self.lon = lon
self.packageWeight = payload
self.avgWattAngleAscendLoaded = 0.0
self.avgWattAngleDescendLoaded = 0.0
self.distanceFromDepot = 0.0
self.timeFromDepot = []
self.timeReturnToDepot = []
self.earliestServiceTime = 0.0
self.maxDelayedServiceTime = 0.0
self.energyconsumptionDronesArrival = []
self.energyconsumptionDronesReturn = []
class Drone:
def __init__(self, dType, numRotors, droneSpeedLoaded, droneSpeedUnloaded, payloadCap, bodyMass, batteryMass, initCharge,
minChargeReq, flyingTimePerMile, batReplaceTime, c_d, c_m, c_bat, avgWattAscendLoaded, avgWattDescendLoaded,
avgWattHoverLoaded, avgWattFlightLoaded, avgWattAscendUnLoaded, avgWattDescendUnLoaded, avgWattHoverUnLoaded,
avgWattFlightUnLoaded):
self.dType = dType
self.numRotors = numRotors
self.optimalSpeedLoaded = droneSpeedLoaded
self.optimalSpeedUnloaded = droneSpeedUnloaded
self.capacity = payloadCap
self.bodyMass = bodyMass
self.batteryMass = batteryMass
self.initCharge = initCharge
self.minChargeReq = minChargeReq
self.allowableEnergy = initCharge - minChargeReq
self.batReplaceTime = batReplaceTime
self.flyingTimePerMile = flyingTimePerMile
self.avgWattAscendLoaded = avgWattAscendLoaded
self.avgWattDescendLoaded = avgWattDescendLoaded
self.avgWattHoverLoaded = avgWattHoverLoaded
self.avgWattFlightLoaded = avgWattFlightLoaded
self.avgWattAscendUnLoaded = avgWattAscendUnLoaded
self.avgWattDescendUnLoaded = avgWattDescendUnLoaded
self.avgWattHoverUnLoaded = avgWattHoverUnLoaded
self.avgWattFlightUnLoaded = avgWattFlightUnLoaded
self.C_d = c_d
self.C_d_M = c_m
self.F_c = c_m + c_d + 480
self.C_bat = c_bat
self.M_g = 2.5*initCharge
self.M_l = -initCharge
self.M_u = initCharge
self.Q_l = -initCharge
self.Q_u = initCharge
def CreateListOfObjects(providerLocation, droneData, deliveryData):
listOfDrones = []
listOfDeliveryLocs = []
provider_df = pd.read_csv(providerLocation)
providerLat = provider_df['lat'][0]
providerLon = provider_df['long'][0]
drone_df = pd.read_csv(droneData)
for row in range(len(drone_df)):
listOfDrones.append(
Drone(drone_df['type'][row], drone_df['numRotors'][row], drone_df['droneSpeedLoaded'][row],
drone_df['droneSpeedUnloaded'][row], drone_df['payloadCap'][row], drone_df['bodyMass'][row],
drone_df['batteryMass'][row], drone_df['initBatCharge'][row], drone_df['minChargeReq'][row],
drone_df['flyingTimePerMile'][row], drone_df['batReplaceTime'][row], drone_df['C_d'][row],
drone_df['C_M'][row],
drone_df['C_bat'][row], drone_df['AvgWattAscendLoaded'][row], drone_df['AvgWattDescendLoaded'][row],
drone_df['AvgWattHoverLoaded'][row], drone_df['AvgWattFlightLoaded'][row],
drone_df['AvgWattAscendUnLoaded'][row],
drone_df['AvgWattDescendUnLoaded'][row], drone_df['AvgWattHoverUnLoaded'][row],
drone_df['AvgWattFlightUnLoaded'][row]))
delivery_df = pd.read_csv(deliveryData)
for row in range(len(delivery_df)):
foodReadyTime = datetime.strptime(delivery_df['food_ready_time'][row],
"%m/%d/%Y %H:%M").timestamp()
listOfDeliveryLocs.append(Node(delivery_df['delivery_id'][row], foodReadyTime, delivery_df['dropoff_lat'][row],
delivery_df['dropoff_long'][row], delivery_df['PackageWeight'][row]))
return listOfDrones, listOfDeliveryLocs, providerLat, providerLon
def computeDistOfEachPair(srclat, srclon, destlat, destlon):
R = 3958.8
rad_srcLat = radians(abs(srclat))
rad_srcLon = radians(abs(srclon))
rad_destLat = radians(abs(destlat))
rad_destLon = radians(abs(destlon))
dLon = rad_destLon - rad_srcLon
dLat = rad_destLat - rad_srcLat
a = sin(dLat / 2) ** 2 + cos(rad_srcLat) * cos(rad_destLat) * sin(dLon / 2) ** 2
c = 2 * atan2(sqrt(a), sqrt(1 - a))
distOfEachPair = R * c
return distOfEachPair
def computeRoadDistanceFromDepot(srclat, srclon, destlat, destlon):
r = requests.get(
f"""http://router.project-osrm.org/route/v1/car/{srclon},{srclat};{destlon},{destlat}?overview=false""")
route = json.loads(r.content)["routes"][0]
drivingDistance = route["distance"] * 0.000621371
travelTimeAPI = (route["duration"])
return drivingDistance, travelTimeAPI
def dataInterpolation(maxLoad, energyLoeaded, energyUnloaded, packageWeight):
calculatedEnergy = energyUnloaded + ((energyLoeaded - energyUnloaded)/maxLoad)*packageWeight
return calculatedEnergy
def computeAscendDescendHoverEnergyLoaded(avgWattAscendLoaded, avgWattAngleAscendLoaded, avgWattDescendLoaded, avgWattAngleDescendLoaded, avgWattHoverLoaded):
ascendEnergyLoaded = avgWattAscendLoaded*durationAscendLoaded*wsecToWattHourConvert*whTokwhConvert
angleAscendEnergyLoaded = avgWattAngleAscendLoaded * durationAngleAscendLoaded * wsecToWattHourConvert * whTokwhConvert
descendEnergyLoaded = avgWattDescendLoaded * durationDescendLoaded * wsecToWattHourConvert * whTokwhConvert
angleDescendEnergyLoaded = avgWattAngleDescendLoaded * durationAngleDescendLoaded * wsecToWattHourConvert * whTokwhConvert
if hoveringBolLoaded == True:
hoverEnergyLoaded = avgWattHoverLoaded * durationHoverLoaded * wsecToWattHourConvert * whTokwhConvert
totalAscendDescendHoverLoaded = ascendEnergyLoaded + angleAscendEnergyLoaded + descendEnergyLoaded + angleDescendEnergyLoaded + hoverEnergyLoaded
else:
totalAscendDescendHoverLoaded = ascendEnergyLoaded + angleAscendEnergyLoaded + descendEnergyLoaded + angleDescendEnergyLoaded
return totalAscendDescendHoverLoaded
def computeAscendDescendHoverEnergyUnloaded(avgWattAscendUnloaded, avgWattAngleAscendUnloaded, avgWattDescendUnloaded, avgWattAngleDescendUnloaded, avgWattHoverUnloaded):
ascendEnergyUnloaded = avgWattAscendUnloaded*durationAscendUnloaded*wsecToWattHourConvert*whTokwhConvert
angleAscendEnergyUnloaded = avgWattAngleAscendUnloaded*durationAngleAscendUnloaded*wsecToWattHourConvert*whTokwhConvert
descendEnergyUnloaded = avgWattDescendUnloaded*durationDescendUnloaded*wsecToWattHourConvert * whTokwhConvert
angleDescendEnergyUnloaded = avgWattAngleDescendUnloaded*durationAngleDescendUnloaded*wsecToWattHourConvert*whTokwhConvert
if hoveringBolUnloaded == True:
hoverEnergyUnloaded = avgWattHoverUnloaded * durationHoverUnloaded * wsecToWattHourConvert * whTokwhConvert
totalAscendDescendHoverUnloaded = ascendEnergyUnloaded + angleAscendEnergyUnloaded + descendEnergyUnloaded + angleDescendEnergyUnloaded + hoverEnergyUnloaded
else:
totalAscendDescendHoverUnloaded = ascendEnergyUnloaded + angleAscendEnergyUnloaded + descendEnergyUnloaded + angleDescendEnergyUnloaded
return totalAscendDescendHoverUnloaded
def computeParams(listOfDrones, listOfDeliveryLocs, providerLat, providerLon, maxPermissibleDelay):
for i in range(len(listOfDeliveryLocs)):
packageWeight = listOfDeliveryLocs[i].packageWeight
listOfDeliveryLocs[i].earliestServiceTime = listOfDeliveryLocs[i].readyTime
listOfDeliveryLocs[i].maxDelayedServiceTime = listOfDeliveryLocs[i].earliestServiceTime + maxPermissibleDelay
destLat = listOfDeliveryLocs[i].lat
destLon = listOfDeliveryLocs[i].lon
distanceFromDepot = computeDistOfEachPair(providerLat, providerLon, destLat, destLon)
listOfDeliveryLocs[i].distanceFromDepot = distanceFromDepot
for d in range(len(listOfDrones)):
flyingTimePerMile = listOfDrones[d].flyingTimePerMile
maxLoad = listOfDrones[d].capacity
if listOfDrones[d].dType == 'DJI':
avgWattAscendLoaded = ascend(packageWeight)
avgWattDescendLoaded = descend(packageWeight)
avgWattHoverLoaded = hover(packageWeight)
avgWattFlightLoaded = forwardFlight(packageWeight)
avgWattAscendUnLoaded = ascend(0)
avgWattDescendUnLoaded = descend(0)
avgWattHoverUnLoaded = hover(0)
avgWattFlightUnLoaded = forwardFlight(0)
else:
avgWattAscendLoaded = dataInterpolation(maxLoad, listOfDrones[d].avgWattAscendLoaded,
listOfDrones[d].avgWattAscendUnLoaded, packageWeight)
avgWattDescendLoaded = dataInterpolation(maxLoad, listOfDrones[d].avgWattDescendLoaded,
listOfDrones[d].avgWattDescendUnLoaded, packageWeight)
avgWattHoverLoaded = dataInterpolation(maxLoad, listOfDrones[d].avgWattHoverLoaded,
listOfDrones[d].avgWattHoverUnLoaded, packageWeight)
avgWattFlightLoaded = dataInterpolation(maxLoad, listOfDrones[d].avgWattFlightLoaded,
listOfDrones[d].avgWattFlightUnLoaded, packageWeight)
avgWattAscendUnLoaded = listOfDrones[d].avgWattAscendUnLoaded
avgWattDescendUnLoaded = listOfDrones[d].avgWattDescendUnLoaded
avgWattHoverUnLoaded = listOfDrones[d].avgWattHoverUnLoaded
avgWattFlightUnLoaded = listOfDrones[d].avgWattFlightUnLoaded
flyingTimeFromDepot = (distanceFromDepot / listOfDrones[
d].optimalSpeedLoaded) * hourToSecConvert
timeFromDepot = flyingTimeFromDepot + durationAscendLoaded + durationAngleAscendLoaded + durationDescendLoaded + durationAngleDescendLoaded + durationHoverLoaded
listOfDeliveryLocs[i].timeFromDepot.append(timeFromDepot)
flyingTimeReturnToDepot = (distanceFromDepot / listOfDrones[
d].optimalSpeedUnloaded) * hourToSecConvert
timeReturnToDepot = flyingTimeReturnToDepot + durationAscendUnloaded + durationAngleAscendUnloaded + durationDescendUnloaded + durationAngleDescendUnloaded + durationHoverUnloaded
listOfDeliveryLocs[i].timeReturnToDepot.append(timeReturnToDepot)
forwardFlightWhPerMileLoaded = (avgWattFlightLoaded * flyingTimePerMile) * wsecToWattHourConvert
energyPerMileLoaded = forwardFlightWhPerMileLoaded * whTokwhConvert
energyConsumptionFlightLoaded = energyPerMileLoaded * distanceFromDepot
forwardFlightWhPerMileUnloaded = (avgWattFlightUnLoaded * flyingTimePerMile) * wsecToWattHourConvert
energyPerMileUnLoaded = forwardFlightWhPerMileUnloaded * whTokwhConvert
energyConsumptionFlightUnLoaded = energyPerMileUnLoaded * distanceFromDepot
ascendDescendHoverEnergyLoaded = computeAscendDescendHoverEnergyLoaded(avgWattAscendLoaded, listOfDeliveryLocs[i].avgWattAngleAscendLoaded, avgWattDescendLoaded, listOfDeliveryLocs[i].avgWattAngleDescendLoaded, avgWattHoverLoaded)
ascendDescendHoverEnergyUnloaded = computeAscendDescendHoverEnergyUnloaded(avgWattAscendUnLoaded, avgWattAngleAscendUnloaded, avgWattDescendUnLoaded, avgWattAngleDescendUnloaded, avgWattHoverUnLoaded)
totalEnergyConsumptionLoaded = energyConsumptionFlightLoaded + ascendDescendHoverEnergyLoaded
totalEnergyConsumptionUnloaded = energyConsumptionFlightUnLoaded + ascendDescendHoverEnergyUnloaded
listOfDeliveryLocs[i].energyconsumptionDronesArrival.append(totalEnergyConsumptionLoaded)
listOfDeliveryLocs[i].energyconsumptionDronesReturn.append(totalEnergyConsumptionUnloaded)
def lisOfObjects(listOfDrones, listOfDeliveryLocs):
eligible = {}
for d in listOfDrones:
eligible[d] = []
index = 0
for d in listOfDrones:
for i in listOfDeliveryLocs:
if (i.packageWeight <= d.capacity) and ((i.energyconsumptionDronesArrival[index] + i.energyconsumptionDronesReturn[index]) <= d.allowableEnergy):
eligible[d].append(i)
index += 1
if droneType == 'Tarot':
listOfDeliveryLocsForTarot = eligible[listOfDrones[0]]
listOfDeliveryLocsForVehicle = [i for i in listOfDeliveryLocs if i not in listOfDeliveryLocsForTarot]
listOfDeliveryLocs = listOfDeliveryLocsForTarot
listOfDrones = [listOfDrones[0]]
elif droneType == 'DJI':
listOfDeliveryLocsForDJI = eligible[listOfDrones[1]]
listOfDeliveryLocsForVehicle = [i for i in listOfDeliveryLocs if i not in listOfDeliveryLocsForDJI]
listOfDeliveryLocs = listOfDeliveryLocsForDJI
listOfDrones = [listOfDrones[1]]
elif droneType == 'Small VTOL':
listOfDeliveryLocsForSmallVTOL = eligible[listOfDrones[2]]
listOfDeliveryLocsForVehicle = [i for i in listOfDeliveryLocs if i not in listOfDeliveryLocsForSmallVTOL]
listOfDeliveryLocs = listOfDeliveryLocsForSmallVTOL
listOfDrones = [listOfDrones[2]]
else:
listOfDeliveryLocsForVTOL = eligible[listOfDrones[3]]
listOfDeliveryLocsForVehicle = [i for i in listOfDeliveryLocs if i not in listOfDeliveryLocsForVTOL]
listOfDeliveryLocs = listOfDeliveryLocsForVTOL
listOfDrones = [listOfDrones[3]]
return listOfDrones, listOfDeliveryLocs, listOfDeliveryLocsForVehicle
def computeParamsForDrone(listOfDrones, listOfDeliveryLocs, providerLat, providerLon, maxPermissibleDelay):
for i in range(len(listOfDeliveryLocs)):
packageWeight = listOfDeliveryLocs[i].packageWeight
listOfDeliveryLocs[i].earliestServiceTime = listOfDeliveryLocs[i].readyTime
listOfDeliveryLocs[i].maxDelayedServiceTime = listOfDeliveryLocs[i].earliestServiceTime + maxPermissibleDelay
destLat = listOfDeliveryLocs[i].lat
destLon = listOfDeliveryLocs[i].lon
distanceFromDepot = computeDistOfEachPair(providerLat, providerLon, destLat, destLon)
listOfDeliveryLocs[i].distanceFromDepot = distanceFromDepot
for d in range(len(listOfDrones)):
flyingTimePerMile = listOfDrones[d].flyingTimePerMile
maxLoad = listOfDrones[d].capacity
if listOfDrones[d].dType == 'DJI':
avgWattAscendLoaded = ascend(packageWeight)
avgWattDescendLoaded = descend(packageWeight)
avgWattHoverLoaded = hover(packageWeight)
avgWattFlightLoaded = forwardFlight(packageWeight)
avgWattAscendUnLoaded = ascend(0)
avgWattDescendUnLoaded = descend(0)
avgWattHoverUnLoaded = hover(0)
avgWattFlightUnLoaded = forwardFlight(0)
else:
avgWattAscendLoaded = dataInterpolation(maxLoad, listOfDrones[d].avgWattAscendLoaded,
listOfDrones[d].avgWattAscendUnLoaded, packageWeight)
avgWattDescendLoaded = dataInterpolation(maxLoad, listOfDrones[d].avgWattDescendLoaded,
listOfDrones[d].avgWattDescendUnLoaded, packageWeight)
avgWattHoverLoaded = dataInterpolation(maxLoad, listOfDrones[d].avgWattHoverLoaded,
listOfDrones[d].avgWattHoverUnLoaded, packageWeight)
avgWattFlightLoaded = dataInterpolation(maxLoad, listOfDrones[d].avgWattFlightLoaded,
listOfDrones[d].avgWattFlightUnLoaded, packageWeight)
avgWattAscendUnLoaded = listOfDrones[d].avgWattAscendUnLoaded
avgWattDescendUnLoaded = listOfDrones[d].avgWattDescendUnLoaded
avgWattHoverUnLoaded = listOfDrones[d].avgWattHoverUnLoaded
avgWattFlightUnLoaded = listOfDrones[d].avgWattFlightUnLoaded
flyingTimeFromDepot = (distanceFromDepot / listOfDrones[
d].optimalSpeedLoaded) * hourToSecConvert
timeFromDepot = flyingTimeFromDepot + durationAscendLoaded + durationAngleAscendLoaded + durationDescendLoaded + durationAngleDescendLoaded + durationHoverLoaded
listOfDeliveryLocs[i].timeFromDepot = timeFromDepot
flyingTimeReturnToDepot = (distanceFromDepot / listOfDrones[
d].optimalSpeedUnloaded) * hourToSecConvert
timeReturnToDepot = flyingTimeReturnToDepot + durationAscendUnloaded + durationAngleAscendUnloaded + durationDescendUnloaded + durationAngleDescendUnloaded + durationHoverUnloaded
listOfDeliveryLocs[i].timeReturnToDepot = timeReturnToDepot
forwardFlightWhPerMileLoaded = (avgWattFlightLoaded * flyingTimePerMile) * wsecToWattHourConvert
energyPerMileLoaded = forwardFlightWhPerMileLoaded * whTokwhConvert
energyConsumptionFlightLoaded = energyPerMileLoaded * distanceFromDepot
forwardFlightWhPerMileUnloaded = (avgWattFlightUnLoaded * flyingTimePerMile) * wsecToWattHourConvert
energyPerMileUnLoaded = forwardFlightWhPerMileUnloaded * whTokwhConvert
energyConsumptionFlightUnLoaded = energyPerMileUnLoaded * distanceFromDepot
ascendDescendHoverEnergyLoaded = computeAscendDescendHoverEnergyLoaded(avgWattAscendLoaded, listOfDeliveryLocs[i].avgWattAngleAscendLoaded, avgWattDescendLoaded, listOfDeliveryLocs[i].avgWattAngleDescendLoaded, avgWattHoverLoaded)
ascendDescendHoverEnergyUnloaded = computeAscendDescendHoverEnergyUnloaded(avgWattAscendUnLoaded, avgWattAngleAscendUnloaded, avgWattDescendUnLoaded, avgWattAngleDescendUnloaded, avgWattHoverUnLoaded)
totalEnergyConsumptionLoaded = energyConsumptionFlightLoaded + ascendDescendHoverEnergyLoaded
totalEnergyConsumptionUnloaded = energyConsumptionFlightUnLoaded + ascendDescendHoverEnergyUnloaded
listOfDeliveryLocs[i].energyconsumptionDronesArrival = totalEnergyConsumptionLoaded
listOfDeliveryLocs[i].energyconsumptionDronesReturn = totalEnergyConsumptionUnloaded
def computeParamsForVehicle(listOfDeliveryLocs, providerLat, providerLon, maxPermissibleDelay):
for i in range(len(listOfDeliveryLocs)):
listOfDeliveryLocs[i].earliestServiceTime = listOfDeliveryLocs[i].readyTime
listOfDeliveryLocs[i].maxDelayedServiceTime = listOfDeliveryLocs[i].earliestServiceTime + maxPermissibleDelay
destLat = listOfDeliveryLocs[i].lat
destLon = listOfDeliveryLocs[i].lon
distanceFromDepot, timeFromDepot = computeRoadDistanceFromDepot(providerLat, providerLon, destLat, destLon)
listOfDeliveryLocs[i].distanceFromDepot = distanceFromDepot
listOfDeliveryLocs[i].timeFromDepot = timeFromDepot
listOfDeliveryLocs[i].timeReturnToDepot = timeFromDepot
totalEnergyConsumptionLoaded = vehicleEnergyConsumptionPerMile*distanceFromDepot
totalEnergyConsumptionUnloaded = vehicleEnergyConsumptionPerMile*distanceFromDepot
listOfDeliveryLocs[i].energyconsumptionDronesArrival = totalEnergyConsumptionLoaded
listOfDeliveryLocs[i].energyconsumptionDronesReturn = totalEnergyConsumptionUnloaded
def createListOfLocsWithDummy(listOfDeliveryLocs):
listOfLocsDummySink = []
if listOfDeliveryLocs:
listOfLocsDummySink.append(Node(0, 0.0, 0.0, 0.0, 0.0))
listOfLocsDummySink[-1].distanceFromDepot = 0.0
listOfLocsDummySink[-1].earliestServiceTime = 0.0
listOfLocsDummySink[-1].maxDelayedServiceTime = 0.0
listOfLocsDummySink[-1].timeFromDepot = 0
listOfLocsDummySink[-1].timeReturnToDepot = 0
listOfLocsDummySink[-1].energyconsumptionDronesArrival = 0
listOfLocsDummySink[-1].energyconsumptionDronesReturn = 0
listOfLocsDummySink.extend(listOfDeliveryLocs)
listOfLocsDummySink.append(Node(-99, 0.0, 0.0, 0.0, 0.0))
listOfLocsDummySink[-1].distanceFromDepot = 0.0
listOfLocsDummySink[-1].earliestServiceTime = 0.0
listOfLocsDummySink[-1].maxDelayedServiceTime = 0.0
listOfLocsDummySink[-1].timeFromDepot = 0
listOfLocsDummySink[-1].timeReturnToDepot = 0
listOfLocsDummySink[-1].energyconsumptionDronesArrival = 0
listOfLocsDummySink[-1].energyconsumptionDronesReturn = 0
return listOfLocsDummySink
def computeRoutingCost(listOfLocsDummySinkForDrone, listOfLocsDummySinkForVehicle, minNumberOfDrones, penaltyOutgoingArcs):
routingCost = {}
for i in range(len(listOfLocsDummySinkForDrone)):
for j in range(len(listOfLocsDummySinkForDrone)):
if listOfLocsDummySinkForDrone[i].deliveryID != listOfLocsDummySinkForDrone[j].deliveryID:
routingCost[listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID] = listOfLocsDummySinkForDrone[i].energyconsumptionDronesReturn+ listOfLocsDummySinkForDrone[j].energyconsumptionDronesArrival
if listOfLocsDummySinkForVehicle:
for i in range(len(listOfLocsDummySinkForVehicle)):
for j in range(len(listOfLocsDummySinkForVehicle)):
if listOfLocsDummySinkForVehicle[i].deliveryID != listOfLocsDummySinkForVehicle[j].deliveryID:
routingCost[listOfLocsDummySinkForVehicle[i].deliveryID, listOfLocsDummySinkForVehicle[j].deliveryID] = listOfLocsDummySinkForVehicle[i].energyconsumptionDronesReturn + listOfLocsDummySinkForVehicle[j].energyconsumptionDronesArrival
if minNumberOfDrones == True:
for key, val in routingCost.items():
if key[0] == 0:
routingCost[key] = val + penaltyOutgoingArcs
return routingCost
def computeTotalEnergyConsumed(zVal, numberOfDronesUsed, routingCost, penaltyOutgoingArcs):
totalEnergy = 0.0
for k, v in zVal.items():
if v > 0.5:
totalEnergy = totalEnergy + routingCost[k]
totalEnergy = totalEnergy - numberOfDronesUsed * penaltyOutgoingArcs
return totalEnergy
def computeMaxEnergyToServeCustomerLoc(listOfDeliveryLocs):
maxEnergyArrivalAllLocs = []
maxEnergyReturnAllLocs = []
for i in range(len(listOfDeliveryLocs)):
maxEnergyArrivalAllLocs.append(max(listOfDeliveryLocs[i].energyconsumptionDronesArrival))
maxEnergyReturnAllLocs.append(max(listOfDeliveryLocs[i].energyconsumptionDronesReturn))
maxTotalEnergyRequired = max(maxEnergyArrivalAllLocs) + max(maxEnergyReturnAllLocs)
return maxTotalEnergyRequired
def computeAvgDistance(listOfDeliveryLocs):
distanceFromDepotInmile = {}
for i in range(len(listOfDeliveryLocs)):
distanceFromDepotInmile[listOfDeliveryLocs[i].deliveryID] = listOfDeliveryLocs[i].distanceFromDepot
sumDistanceAllLocations = sum(distanceFromDepotInmile.values())
avgDistanceAllLocations = sumDistanceAllLocations / len(listOfDeliveryLocs)
return avgDistanceAllLocations
def computePenaltyFindingRedundantPairs(listOfDeliveryLocs, listOfDeliveryLocsForVehicle):
if not listOfDeliveryLocs:
maxTimeFromDepot = max([i.timeFromDepot for i in listOfDeliveryLocsForVehicle])
elif not listOfDeliveryLocsForVehicle:
maxTimeFromDepot = max([i.timeFromDepot for i in listOfDeliveryLocs])
else:
maxTimeFromDepot = max(max([i.timeFromDepot for i in listOfDeliveryLocs]), max([i.timeFromDepot for i in listOfDeliveryLocsForVehicle]))
return maxTimeFromDepot
def computeUnnecessaryPairs(listOfDeliveryLocs, listOfDeliveryLocsForVehicle, maxPermissibleDelay, penaltyTime):
listOfUnnecessaryPairs = []
for i in range(len(listOfDeliveryLocs)):
for j in range(len(listOfDeliveryLocs)):
if ((listOfDeliveryLocs[i].earliestServiceTime + packageLoadingTime + listOfDeliveryLocs[i].timeFromDepot
+ listOfDeliveryLocs[i].timeReturnToDepot + packageUnloadingTimeLanding) >= (
listOfDeliveryLocs[j].earliestServiceTime + maxPermissibleDelay)) or (
listOfDeliveryLocs[j].earliestServiceTime > (
listOfDeliveryLocs[i].earliestServiceTime + maxPermissibleDelay +
listOfDeliveryLocs[i].timeFromDepot + listOfDeliveryLocs[i].timeReturnToDepot
+ packageLoadingTime + packageUnloadingTimeLanding + penaltyTime)):
listOfUnnecessaryPairs.append((listOfDeliveryLocs[i].deliveryID, listOfDeliveryLocs[j].deliveryID))
for i in range(len(listOfDeliveryLocsForVehicle)):
for j in range(len(listOfDeliveryLocsForVehicle)):
if ((listOfDeliveryLocsForVehicle[i].earliestServiceTime + packageLoadingTime + listOfDeliveryLocsForVehicle[i].timeFromDepot
+ listOfDeliveryLocsForVehicle[i].timeReturnToDepot + packageUnloadingTimeLanding) >= (
listOfDeliveryLocsForVehicle[j].earliestServiceTime + maxPermissibleDelay)) or (
listOfDeliveryLocsForVehicle[j].earliestServiceTime > (
listOfDeliveryLocsForVehicle[i].earliestServiceTime + maxPermissibleDelay +
listOfDeliveryLocsForVehicle[i].timeFromDepot + listOfDeliveryLocsForVehicle[i].timeReturnToDepot
+ packageLoadingTime + packageUnloadingTimeLanding + penaltyTime)):
listOfUnnecessaryPairs.append((listOfDeliveryLocsForVehicle[i].deliveryID, listOfDeliveryLocsForVehicle[j].deliveryID))
return listOfUnnecessaryPairs
def computeNumberOfDronesUsed(zVal):
outgoingArcsFromDepotDict = {}
for key, value in zVal.items():
if key[0] == 0 and value > 0.5:
outgoingArcsFromDepotDict[key] = value
numberOfDronesUsed = len(outgoingArcsFromDepotDict)
return numberOfDronesUsed, outgoingArcsFromDepotDict
def computeNumberOfBatteriesReplaced(yVal):
numOfBatteryReplaced = 0.0
for key, value in yVal.items():
if value > 0.5:
numOfBatteryReplaced = numOfBatteryReplaced + 1.0
return numOfBatteryReplaced
def findOptimalRoutes(zVal):
dictSrcDests = dict()
for k, v in zVal.items():
if v > 0.5:
if k[0] in dictSrcDests:
dictSrcDests[k[0]].append(k[1])
else:
dictSrcDests[k[0]] = [k[1]]
routes = list()
nextNodesFrom0 = dictSrcDests[0]
for i in nextNodesFrom0:
tempRoute = [0, i]
while True:
nextNode = dictSrcDests[i][0]
if nextNode != -99:
tempRoute.append(nextNode)
i = nextNode
else:
tempRoute.append(0)
routes.append(tempRoute)
break
return routes
def createMIPmodel(listOfLocsDummySinkForDrone, listOfLocsDummySinkForVehicle, listOfDrones, routingCost, listOfUnnecessaryPairs):
initBatCharge = listOfDrones[0].initCharge
minChargeReq = listOfDrones[0].minChargeReq
C_d = listOfDrones[0].C_d
C_d_M = listOfDrones[0].C_d_M
M_g = listOfDrones[0].M_g
M_l = listOfDrones[0].M_l
M_u = listOfDrones[0].M_u
Q_l = listOfDrones[0].Q_l
Q_u = listOfDrones[0].Q_u
C_bat = listOfDrones[0].C_bat
batReplaceTime = listOfDrones[0].batReplaceTime
tm = Model(name='minTransCost_IdenticalDrones_CompactModel')
tm.parameters.mip.tolerances.mipgap.set(gap)
y = {}
for i in range(len(listOfLocsDummySinkForDrone)):
y[listOfLocsDummySinkForDrone[i].deliveryID] = tm.binary_var(
name='y_' + str(listOfLocsDummySinkForDrone[i].deliveryID))
g = {}
for i in range(len(listOfLocsDummySinkForDrone)):
g[listOfLocsDummySinkForDrone[i].deliveryID] = tm.continuous_var(lb=0, ub=initBatCharge,
name='g_' + str(
listOfLocsDummySinkForDrone[i].deliveryID))
g_prime = {}
for i in range(len(listOfLocsDummySinkForDrone)):
g_prime[listOfLocsDummySinkForDrone[i].deliveryID] = tm.continuous_var(lb=-initBatCharge, ub=initBatCharge,
name='g_prime_' + str(
listOfLocsDummySinkForDrone[
i].deliveryID))
f = {}
for i in range(len(listOfLocsDummySinkForDrone)):
f[listOfLocsDummySinkForDrone[i].deliveryID] = tm.continuous_var(lb=0,
name='f_' + str(
listOfLocsDummySinkForDrone[i].deliveryID))
z = {}
for i in range(len(listOfLocsDummySinkForDrone)):
for j in range(len(listOfLocsDummySinkForDrone)):
if (listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID) not in listOfUnnecessaryPairs:
if listOfLocsDummySinkForDrone[i].deliveryID != listOfLocsDummySinkForDrone[j].deliveryID:
z[listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID] = tm.binary_var(
name='z_' + str(listOfLocsDummySinkForDrone[i].deliveryID) + '_' + str(
listOfLocsDummySinkForDrone[j].deliveryID))
if listOfLocsDummySinkForVehicle:
x = {}
for i in range(len(listOfLocsDummySinkForVehicle)):
for j in range(len(listOfLocsDummySinkForVehicle)):
if (listOfLocsDummySinkForVehicle[i].deliveryID,
listOfLocsDummySinkForVehicle[j].deliveryID) not in listOfUnnecessaryPairs:
if listOfLocsDummySinkForVehicle[i].deliveryID != listOfLocsDummySinkForVehicle[j].deliveryID:
x[listOfLocsDummySinkForVehicle[i].deliveryID, listOfLocsDummySinkForVehicle[
j].deliveryID] = tm.binary_var(
name='x_' + str(listOfLocsDummySinkForVehicle[i].deliveryID) + '_' + str(
listOfLocsDummySinkForVehicle[j].deliveryID))
f_v = {}
for i in range(len(listOfLocsDummySinkForVehicle)):
f_v[listOfLocsDummySinkForVehicle[i].deliveryID] = tm.continuous_var(lb=0,
name='f_v_' + str(
listOfLocsDummySinkForVehicle[
i].deliveryID))
if batteryReplacement == True:
tm.minimize(C_E * tm.sum(routingCost[listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID] * z[
listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID]
for i in range(0, len(listOfLocsDummySinkForDrone) - 1) for j in
range(1, len(listOfLocsDummySinkForDrone)) if ((listOfLocsDummySinkForDrone[i].deliveryID,
listOfLocsDummySinkForDrone[
j].deliveryID) not in listOfUnnecessaryPairs) and (
listOfLocsDummySinkForDrone[i].deliveryID != listOfLocsDummySinkForDrone[j].deliveryID))
+ C_E * tm.sum(routingCost[listOfLocsDummySinkForVehicle[i].deliveryID, listOfLocsDummySinkForVehicle[j].deliveryID] * x[
listOfLocsDummySinkForVehicle[i].deliveryID, listOfLocsDummySinkForVehicle[j].deliveryID]
for i in range(0, len(listOfLocsDummySinkForVehicle) - 1) for j in
range(1, len(listOfLocsDummySinkForVehicle)) if ((listOfLocsDummySinkForVehicle[i].deliveryID,
listOfLocsDummySinkForVehicle[
j].deliveryID) not in listOfUnnecessaryPairs) and (
listOfLocsDummySinkForVehicle[i].deliveryID != listOfLocsDummySinkForVehicle[j].deliveryID))
+ (C_d + C_L_d + C_d_M) * tm.sum(
z[0, listOfLocsDummySinkForDrone[j].deliveryID] for j in range(1, len(listOfLocsDummySinkForDrone)))
+ (C_v + C_lv + C_mv) * tm.sum(
x[0, listOfLocsDummySinkForVehicle[j].deliveryID] for j in range(1, len(listOfLocsDummySinkForVehicle)))
+ C_bat * tm.sum(y[listOfLocsDummySinkForDrone[i].deliveryID] for i in range(len(listOfLocsDummySinkForDrone))))
else:
tm.minimize(C_E * tm.sum(
routingCost[listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID] * z[
listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID]
for i in range(0, len(listOfLocsDummySinkForDrone) - 1) for j in
range(1, len(listOfLocsDummySinkForDrone)) if ((listOfLocsDummySinkForDrone[i].deliveryID,
listOfLocsDummySinkForDrone[
j].deliveryID) not in listOfUnnecessaryPairs) and (
listOfLocsDummySinkForDrone[i].deliveryID != listOfLocsDummySinkForDrone[j].deliveryID))
+ C_E * tm.sum(
routingCost[listOfLocsDummySinkForVehicle[i].deliveryID, listOfLocsDummySinkForVehicle[j].deliveryID] *
x[
listOfLocsDummySinkForVehicle[i].deliveryID, listOfLocsDummySinkForVehicle[j].deliveryID]
for i in range(0, len(listOfLocsDummySinkForVehicle) - 1) for j in
range(1, len(listOfLocsDummySinkForVehicle)) if ((listOfLocsDummySinkForVehicle[i].deliveryID,
listOfLocsDummySinkForVehicle[
j].deliveryID) not in listOfUnnecessaryPairs) and (
listOfLocsDummySinkForVehicle[i].deliveryID != listOfLocsDummySinkForVehicle[j].deliveryID))
+ (C_d + C_L_d + C_d_M) * tm.sum(
z[0, listOfLocsDummySinkForDrone[j].deliveryID] for j in range(1, len(listOfLocsDummySinkForDrone)))
+ (C_v + C_lv + C_mv) * tm.sum(
x[0, listOfLocsDummySinkForVehicle[j].deliveryID] for j in range(1, len(listOfLocsDummySinkForVehicle))))
else:
if batteryReplacement == True:
tm.minimize(C_E * tm.sum(routingCost[listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID] * z[
listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID]
for i in range(0, len(listOfLocsDummySinkForDrone) - 1) for j in
range(1, len(listOfLocsDummySinkForDrone)) if ((listOfLocsDummySinkForDrone[i].deliveryID,
listOfLocsDummySinkForDrone[
j].deliveryID) not in listOfUnnecessaryPairs) and (
listOfLocsDummySinkForDrone[i].deliveryID != listOfLocsDummySinkForDrone[j].deliveryID))
+ (C_d + C_L_d + C_d_M) * tm.sum(
z[0, listOfLocsDummySinkForDrone[j].deliveryID] for j in range(1, len(listOfLocsDummySinkForDrone)))
+ C_bat * tm.sum(y[listOfLocsDummySinkForDrone[i].deliveryID] for i in range(len(listOfLocsDummySinkForDrone))))
else:
tm.minimize(C_E * tm.sum(routingCost[listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID] * z[
listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID]
for i in range(0, len(listOfLocsDummySinkForDrone) - 1) for j in
range(1, len(listOfLocsDummySinkForDrone)) if ((listOfLocsDummySinkForDrone[i].deliveryID,
listOfLocsDummySinkForDrone[
j].deliveryID) not in listOfUnnecessaryPairs) and (
listOfLocsDummySinkForDrone[i].deliveryID != listOfLocsDummySinkForDrone[j].deliveryID))
+ (C_d + C_L_d + C_d_M) * tm.sum(
z[0, listOfLocsDummySinkForDrone[j].deliveryID] for j in range(1, len(listOfLocsDummySinkForDrone))))
for j in range(1, len(listOfLocsDummySinkForDrone)):
tm.add_constraint(f[listOfLocsDummySinkForDrone[j].deliveryID] >= (t_0 + listOfLocsDummySinkForDrone[j].timeFromDepot
- M * (1 - z[0, listOfLocsDummySinkForDrone[j].deliveryID])),
ctname='cnstr10_' + str(listOfLocsDummySinkForDrone[j].deliveryID))
for i in range(1, len(listOfLocsDummySinkForDrone)):
for j in range(1, len(listOfLocsDummySinkForDrone)):
if (listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID) not in listOfUnnecessaryPairs:
if listOfLocsDummySinkForDrone[i].deliveryID != listOfLocsDummySinkForDrone[j].deliveryID:
if packageDropping == True:
tm.add_constraint(f[listOfLocsDummySinkForDrone[j].deliveryID] >= (
f[listOfLocsDummySinkForDrone[i].deliveryID] + packageUnloadingTimeLanding +
listOfLocsDummySinkForDrone[i].timeReturnToDepot + packageLoadingTime +
listOfLocsDummySinkForDrone[j].timeFromDepot + batReplaceTime * y[
listOfLocsDummySinkForDrone[i].deliveryID] -
M * (1 - z[listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID])),
ctname='cnstr11_' + str(listOfLocsDummySinkForDrone[i].deliveryID) + str(
listOfLocsDummySinkForDrone[j].deliveryID))
else:
tm.add_constraint(f[listOfLocsDummySinkForDrone[j].deliveryID] >= (
f[listOfLocsDummySinkForDrone[i].deliveryID] + packageUnloadingTimeLanding +
listOfLocsDummySinkForDrone[i].timeReturnToDepot
+ packageLoadingTime +
listOfLocsDummySinkForDrone[j].timeFromDepot + batReplaceTime * y[
listOfLocsDummySinkForDrone[i].deliveryID] -
M * (1 - z[
listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID])),
ctname='cnstr11_' + str(listOfLocsDummySinkForDrone[i].deliveryID) + str(
listOfLocsDummySinkForDrone[j].deliveryID))
for i in range(1, len(listOfLocsDummySinkForDrone) - 1):
tm.add_constraint(f[listOfLocsDummySinkForDrone[i].deliveryID] >= listOfLocsDummySinkForDrone[i].earliestServiceTime,
ctname='cnstr12_' + str(listOfLocsDummySinkForDrone[i].deliveryID))
tm.add_constraint(f[listOfLocsDummySinkForDrone[i].deliveryID] <= listOfLocsDummySinkForDrone[i].maxDelayedServiceTime,
ctname='cnstr13_' + str(listOfLocsDummySinkForDrone[i].deliveryID))
for j in range(1, len(listOfLocsDummySinkForDrone) - 1):
tm.add_constraint(tm.sum(z[listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID]
for i in range(0, len(listOfLocsDummySinkForDrone) - 1) if ((listOfLocsDummySinkForDrone[i].deliveryID,
listOfLocsDummySinkForDrone[
j].deliveryID) not in listOfUnnecessaryPairs) and (
listOfLocsDummySinkForDrone[i].deliveryID != listOfLocsDummySinkForDrone[j].deliveryID))
== tm.sum(z[listOfLocsDummySinkForDrone[j].deliveryID, listOfLocsDummySinkForDrone[i].deliveryID]
for i in range(1, len(listOfLocsDummySinkForDrone)) if ((listOfLocsDummySinkForDrone[j].deliveryID,
listOfLocsDummySinkForDrone[
i].deliveryID) not in listOfUnnecessaryPairs) and (
listOfLocsDummySinkForDrone[i].deliveryID != listOfLocsDummySinkForDrone[
j].deliveryID)))
tm.add_constraint(tm.sum(z[0, listOfLocsDummySinkForDrone[j].deliveryID] for j in range(1, len(listOfLocsDummySinkForDrone) - 1)) ==
tm.sum(z[listOfLocsDummySinkForDrone[j].deliveryID, -99] for j in range(1, len(listOfLocsDummySinkForDrone) - 1)))
for j in range(1, len(listOfLocsDummySinkForDrone) - 1):
tm.add_constraint(tm.sum(z[listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID]
for i in range(0, len(listOfLocsDummySinkForDrone) - 1) if ((listOfLocsDummySinkForDrone[i].deliveryID,
listOfLocsDummySinkForDrone[
j].deliveryID) not in listOfUnnecessaryPairs) and (
listOfLocsDummySinkForDrone[i].deliveryID != listOfLocsDummySinkForDrone[
j].deliveryID)) == 1)
for i in range(1, len(listOfLocsDummySinkForDrone) - 1):
tm.add_constraint(tm.sum(z[listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID]
for j in range(1, len(listOfLocsDummySinkForDrone)) if ((listOfLocsDummySinkForDrone[i].deliveryID,
listOfLocsDummySinkForDrone[
j].deliveryID) not in listOfUnnecessaryPairs) and (
listOfLocsDummySinkForDrone[i].deliveryID != listOfLocsDummySinkForDrone[
j].deliveryID)) == 1)
if listOfLocsDummySinkForVehicle:
for j in range(1, len(listOfLocsDummySinkForVehicle)):
tm.add_constraint(
f_v[listOfLocsDummySinkForVehicle[j].deliveryID] >= (t_0 + listOfLocsDummySinkForVehicle[j].timeFromDepot
- M * (1 - x[
0, listOfLocsDummySinkForVehicle[j].deliveryID])),
ctname='cnstr10_' + str(listOfLocsDummySinkForVehicle[j].deliveryID))
for i in range(1, len(listOfLocsDummySinkForVehicle)):
for j in range(1, len(listOfLocsDummySinkForVehicle)):
if (listOfLocsDummySinkForVehicle[i].deliveryID,
listOfLocsDummySinkForVehicle[j].deliveryID) not in listOfUnnecessaryPairs:
if listOfLocsDummySinkForVehicle[i].deliveryID != listOfLocsDummySinkForVehicle[j].deliveryID:
tm.add_constraint(f_v[listOfLocsDummySinkForVehicle[j].deliveryID] >= (
f_v[listOfLocsDummySinkForVehicle[i].deliveryID] + packageUnloadingTimeVehicle +
listOfLocsDummySinkForVehicle[i].timeReturnToDepot + packageLoadingTimeVehicle +
listOfLocsDummySinkForVehicle[j].timeFromDepot -
M * (1 - x[
listOfLocsDummySinkForVehicle[i].deliveryID, listOfLocsDummySinkForVehicle[j].deliveryID])),
ctname='cnstr11_' + str(listOfLocsDummySinkForVehicle[i].deliveryID) + str(
listOfLocsDummySinkForVehicle[j].deliveryID))
for i in range(1, len(listOfLocsDummySinkForVehicle) - 1):
tm.add_constraint(
f_v[listOfLocsDummySinkForVehicle[i].deliveryID] >= listOfLocsDummySinkForVehicle[i].earliestServiceTime,
ctname='cnstr12_' + str(listOfLocsDummySinkForVehicle[i].deliveryID))
tm.add_constraint(
f_v[listOfLocsDummySinkForVehicle[i].deliveryID] <= listOfLocsDummySinkForVehicle[i].maxDelayedServiceTime,
ctname='cnstr13_' + str(listOfLocsDummySinkForVehicle[i].deliveryID))
for j in range(1, len(listOfLocsDummySinkForVehicle) - 1):
tm.add_constraint(
tm.sum(x[listOfLocsDummySinkForVehicle[i].deliveryID, listOfLocsDummySinkForVehicle[j].deliveryID]
for i in range(0, len(listOfLocsDummySinkForVehicle) - 1) if
((listOfLocsDummySinkForVehicle[i].deliveryID,
listOfLocsDummySinkForVehicle[
j].deliveryID) not in listOfUnnecessaryPairs) and (
listOfLocsDummySinkForVehicle[i].deliveryID != listOfLocsDummySinkForVehicle[j].deliveryID))
== tm.sum(x[listOfLocsDummySinkForVehicle[j].deliveryID, listOfLocsDummySinkForVehicle[i].deliveryID]
for i in range(1, len(listOfLocsDummySinkForVehicle)) if
((listOfLocsDummySinkForVehicle[j].deliveryID,
listOfLocsDummySinkForVehicle[
i].deliveryID) not in listOfUnnecessaryPairs) and (
listOfLocsDummySinkForVehicle[i].deliveryID != listOfLocsDummySinkForVehicle[
j].deliveryID)))
tm.add_constraint(tm.sum(
x[0, listOfLocsDummySinkForVehicle[j].deliveryID] for j in range(1, len(listOfLocsDummySinkForVehicle) - 1)) ==
tm.sum(x[listOfLocsDummySinkForVehicle[j].deliveryID, -99] for j in
range(1, len(listOfLocsDummySinkForVehicle) - 1)))
for j in range(1, len(listOfLocsDummySinkForVehicle) - 1):
tm.add_constraint(
tm.sum(x[listOfLocsDummySinkForVehicle[i].deliveryID, listOfLocsDummySinkForVehicle[j].deliveryID]
for i in range(0, len(listOfLocsDummySinkForVehicle) - 1) if
((listOfLocsDummySinkForVehicle[i].deliveryID,
listOfLocsDummySinkForVehicle[
j].deliveryID) not in listOfUnnecessaryPairs) and (
listOfLocsDummySinkForVehicle[i].deliveryID != listOfLocsDummySinkForVehicle[
j].deliveryID)) == 1)
for i in range(1, len(listOfLocsDummySinkForVehicle) - 1):
tm.add_constraint(
tm.sum(x[listOfLocsDummySinkForVehicle[i].deliveryID, listOfLocsDummySinkForVehicle[j].deliveryID]
for j in range(1, len(listOfLocsDummySinkForVehicle)) if
((listOfLocsDummySinkForVehicle[i].deliveryID,
listOfLocsDummySinkForVehicle[
j].deliveryID) not in listOfUnnecessaryPairs) and (
listOfLocsDummySinkForVehicle[i].deliveryID != listOfLocsDummySinkForVehicle[
j].deliveryID)) == 1)
if batteryReplacement == True:
for j in range(1, len(listOfLocsDummySinkForDrone)):
tm.add_constraint(g_prime[listOfLocsDummySinkForDrone[j].deliveryID] <= initBatCharge -
(listOfLocsDummySinkForDrone[j].energyconsumptionDronesArrival +
listOfLocsDummySinkForDrone[j].energyconsumptionDronesReturn)
+ M_g * (1 - z[0, listOfLocsDummySinkForDrone[j].deliveryID]),
ctname='cnstr14_' + str(listOfLocsDummySinkForDrone[j].deliveryID))
for i in range(1, len(listOfLocsDummySinkForDrone) - 1):
for j in range(1, len(listOfLocsDummySinkForDrone)):
if (listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID) not in listOfUnnecessaryPairs:
if listOfLocsDummySinkForDrone[i].deliveryID != listOfLocsDummySinkForDrone[j].deliveryID:
tm.add_constraint(
g_prime[listOfLocsDummySinkForDrone[j].deliveryID] <= g[listOfLocsDummySinkForDrone[i].deliveryID] -
(listOfLocsDummySinkForDrone[j].energyconsumptionDronesArrival +
listOfLocsDummySinkForDrone[j].energyconsumptionDronesReturn) +
M_g * (1 - z[listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID]),
ctname='cnstr15_' + str(listOfLocsDummySinkForDrone[i].deliveryID) + '_' + str(
listOfLocsDummySinkForDrone[j].deliveryID))
for i in range(0, len(listOfLocsDummySinkForDrone) - 1):
for j in range(1, len(listOfLocsDummySinkForDrone)):
if (listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID) not in listOfUnnecessaryPairs:
if listOfLocsDummySinkForDrone[i].deliveryID != listOfLocsDummySinkForDrone[j].deliveryID:
tm.add_constraint(g_prime[listOfLocsDummySinkForDrone[j].deliveryID] - minChargeReq >=
M_l * y[listOfLocsDummySinkForDrone[i].deliveryID] +
M_g * (z[listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[
j].deliveryID] - 1),
ctname='cnstr16_' + str(listOfLocsDummySinkForDrone[i].deliveryID) + '_' + str(
listOfLocsDummySinkForDrone[j].deliveryID))
tm.add_constraint(g_prime[listOfLocsDummySinkForDrone[j].deliveryID] - minChargeReq <=
M_u * (1 - y[listOfLocsDummySinkForDrone[i].deliveryID]) +
M_g * (1 - z[
listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID]),
ctname='cnstr17_' + str(listOfLocsDummySinkForDrone[i].deliveryID) + '_' + str(
listOfLocsDummySinkForDrone[j].deliveryID))
tm.add_constraint(g[listOfLocsDummySinkForDrone[j].deliveryID] <= initBatCharge
- (listOfLocsDummySinkForDrone[j].energyconsumptionDronesArrival +
listOfLocsDummySinkForDrone[j].energyconsumptionDronesReturn)
+ Q_u * (1 - y[listOfLocsDummySinkForDrone[i].deliveryID]) +
M_g * (1 - z[
listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID])
, ctname='cnstr18_' + str(listOfLocsDummySinkForDrone[i].deliveryID) + '_' + str(
listOfLocsDummySinkForDrone[j].deliveryID))
for i in range(1, len(listOfLocsDummySinkForDrone) - 1):
for j in range(1, len(listOfLocsDummySinkForDrone)):
if (listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID) not in listOfUnnecessaryPairs:
if listOfLocsDummySinkForDrone[i].deliveryID != listOfLocsDummySinkForDrone[j].deliveryID:
tm.add_constraint(g[listOfLocsDummySinkForDrone[j].deliveryID] <= g[listOfLocsDummySinkForDrone[i].deliveryID] -
(listOfLocsDummySinkForDrone[j].energyconsumptionDronesArrival +
listOfLocsDummySinkForDrone[j].energyconsumptionDronesReturn)
+ Q_u * y[listOfLocsDummySinkForDrone[i].deliveryID] +
M_g * (1 - z[
listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID]),
ctname='cnstr19_' + str(listOfLocsDummySinkForDrone[i].deliveryID) + '_' + str(
listOfLocsDummySinkForDrone[j].deliveryID))
for j in range(1, len(listOfLocsDummySinkForDrone)):
tm.add_constraint(g[listOfLocsDummySinkForDrone[j].deliveryID] <= initBatCharge
- (listOfLocsDummySinkForDrone[j].energyconsumptionDronesArrival +
listOfLocsDummySinkForDrone[j].energyconsumptionDronesReturn)
+ Q_u * y[0] +
M_g * (1 - z[0, listOfLocsDummySinkForDrone[j].deliveryID])
, ctname='cnstr18_' + str(listOfLocsDummySinkForDrone[j].deliveryID))
tm.print_information()
with open('Model(New).txt', 'w') as file:
file.write(tm.lp_string)
file.write('\n----------------------------------------------------------------------------------------------')
file.write('\n')
file.write("\nList of unnecessary pairs: %s" % listOfUnnecessaryPairs)
start_time = time.time()
tms = tm.solve()
runtime = (time.time() - start_time)
mipGap = tm.parameters.mip.tolerances.mipgap.get()
objVal = tms.objective_value
fVal = {}
for i in range(1, len(listOfLocsDummySinkForDrone) - 1):
dt1 = datetime.fromtimestamp(tms[f[listOfLocsDummySinkForDrone[i].deliveryID]])
dtVar = dt1.strftime("%m/%d/%Y %I:%M:%S %p")
fVal[listOfLocsDummySinkForDrone[i].deliveryID] = dtVar
zVal = {}
for i in range(len(listOfLocsDummySinkForDrone)):
for j in range(len(listOfLocsDummySinkForDrone)):
if (listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID) not in listOfUnnecessaryPairs:
if listOfLocsDummySinkForDrone[i].deliveryID != listOfLocsDummySinkForDrone[j].deliveryID:
if tms[z[listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID]] > 0.0:
zVal[listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID] = tms[
z[listOfLocsDummySinkForDrone[i].deliveryID, listOfLocsDummySinkForDrone[j].deliveryID]]
if listOfLocsDummySinkForVehicle:
f_vVal = {}
for i in range(1, len(listOfLocsDummySinkForVehicle) - 1):
dt1 = datetime.fromtimestamp(tms[f_v[listOfLocsDummySinkForVehicle[i].deliveryID]])
dtVar = dt1.strftime("%m/%d/%Y %I:%M:%S %p")