#Rebalancing operations
data_dict = Rebalancing.getInputData(nSt=NumberOfStations,
nTr=k,
CapTr=TruckCapacity,
desiredConfig=ConfigIni,
currentConfig=ConfigFin)
t1_reb = time.time()
UnknownCost.append(Rebalancing.Solve(data_dict, TimeLimit))
t2_reb = time.time()
UnknownRebTime.append(round(t2_reb - t1_reb, 2))
elif demand_is == 'Known':
#Estimate Configuration of the day based on the popularity of the stations forecasted
ConfigIni = Simulation.EstimateConfigIni(j)
#Simulation
t1_sim = time.time()
ConfigFin, LostDemand = Simulation.Simulate(
InitialConfiguration=ConfigIni, scenario=j)
t2_sim = time.time()
KnownSimTime.append(round(t2_sim - t1_sim, 2))
KnownConfigIniList.append(ConfigIni)
KnownConfigFinList.append(ConfigFin)
KnownLostDemandList.append(LostDemand)
#Rebalancing operations
ConfigNextDay = Simulation.EstimateConfigIni(jj)
data_dict = Rebalancing.getInputData(
