Conversion of very simple Gurobi-based code to Pulp

[gelazari]

Hi all,

I'm new to Pulp and have been trying to convert a simple Gurobi-based code snippet to Pulp with no success unfortunately. Any help would be highly appreciated so I can study the code and slowly transition to Pulp completely. Please find my very simple driver-scheduling script in Gurobi. Thank you for your time.

import pandas as pd
import numpy as np
from gurobipy import *

shiftList = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']
workerList = ['Driver_1', 'Driver_2', 'Driver_3', 'Driver_4', 'Driver_5']

shiftReq = [2, 2, 4, 2, 5, 4, 5]
shiftRequirements = {s: shiftReq[i] for i, s in enumerate(shiftList)}

# Assume everyone is available
availability = pd.DataFrame(np.ones((len(workerList), len(shiftList))), index=workerList,
                            columns=shiftList)

# Create availability dictionary to be used in decision variable bounding
avail = {(w, s): availability.loc[w, s] for w in workerList for s in shiftList}

mgmtList = []
nonmgmtList = [x for x in workerList if x not in mgmtList]

# Range of shifts that every workers is required to stay between
minShifts = 2
maxShifts = 6

model = Model("Workers Scheduling")

# ub ensures that workers are only staffed when they are available
x = model.addVars(workerList, shiftList, ub=avail, vtype=GRB.BINARY, name='x')

regHours = model.addVars(workerList, name='regHrs')

# Ensure proper number of workers are scheduled

shiftReq = model.addConstrs((
    (x.sum('*', s) == shiftRequirements[s] for s in shiftList)
), name='shiftRequirement')


# Decompose total shifts for each worker into regular shifts and OT shifts
regOT1 = model.addConstrs((regHours[w] == x.sum(w, '*') for w in workerList))

# Ensure each worker stays within min and max shift bounds

minShiftsConstr = model.addConstrs(((x.sum(w, '*') >= minShifts for w in workerList)),
                                   name='minShifts')

maxShiftsConstr = model.addConstrs(((x.sum(w, '*') <= maxShifts for w in workerList)),
                                   name='maxShifts')

# Minimize total cost, accounting for pay difference between regular time and overtime

model.ModelSense = GRB.MINIMIZE

Cost = 0
Cost += (quicksum(regHours[w] for w in workerList))

model.setObjective(Cost)

model.optimize()

sol = pd.DataFrame(data={'Solution': model.X}, index=model.VarName)
sol = sol.iloc[0:len(x)]

dashboard = pd.DataFrame(index=workerList, columns=shiftList)
for w in workerList:
    for s in shiftList:
        dashboard.at[w, s] = sol.loc['x[' + w + ',' + s + ']',][0]

print(dashboard)

shiftAssignments = {}
for s in shiftList:
    shiftAssignments.update({s: list(dashboard[dashboard[s] == 1].loc[:, ].index)})

print(shiftAssignments)