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workforce4_cs.cs
/* Copyright 2024, Gurobi Optimization, LLC */
/* Assign workers to shifts; each worker may or may not be available on a
particular day. We use Pareto optimization to solve the model:
first, we minimize the linear sum of the slacks. Then, we constrain
the sum of the slacks, and we minimize a quadratic objective that
tries to balance the workload among the workers. */
using System;
using Gurobi;
class workforce4_cs
{
static void Main()
{
try {
// Sample data
// Sets of days and workers
string[] Shifts =
new string[] { "Mon1", "Tue2", "Wed3", "Thu4", "Fri5", "Sat6",
"Sun7", "Mon8", "Tue9", "Wed10", "Thu11", "Fri12", "Sat13",
"Sun14" };
string[] Workers =
new string[] { "Amy", "Bob", "Cathy", "Dan", "Ed", "Fred", "Gu" };
int nShifts = Shifts.Length;
int nWorkers = Workers.Length;
// Number of workers required for each shift
double[] shiftRequirements =
new double[] { 3, 2, 4, 4, 5, 6, 5, 2, 2, 3, 4, 6, 7, 5 };
// Worker availability: 0 if the worker is unavailable for a shift
double[,] availability =
new double[,] { { 0, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1 },
{ 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0 },
{ 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1 },
{ 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1 },
{ 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1 },
{ 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1 },
{ 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 } };
// Model
GRBEnv env = new GRBEnv();
GRBModel model = new GRBModel(env);
model.ModelName = "assignment";
// Assignment variables: x[w][s] == 1 if worker w is assigned
// to shift s. This is no longer a pure assignment model, so we must
// use binary variables.
GRBVar[,] x = new GRBVar[nWorkers, nShifts];
for (int w = 0; w < nWorkers; ++w) {
for (int s = 0; s < nShifts; ++s) {
x[w,s] =
model.AddVar(0, availability[w,s], 0, GRB.BINARY,
Workers[w] + "." + Shifts[s]);
}
}
// Slack variables for each shift constraint so that the shifts can
// be satisfied
GRBVar[] slacks = new GRBVar[nShifts];
for (int s = 0; s < nShifts; ++s) {
slacks[s] =
model.AddVar(0, GRB.INFINITY, 0, GRB.CONTINUOUS,
Shifts[s] + "Slack");
}
// Variable to represent the total slack
GRBVar totSlack = model.AddVar(0, GRB.INFINITY, 0, GRB.CONTINUOUS,
"totSlack");
// Variables to count the total shifts worked by each worker
GRBVar[] totShifts = new GRBVar[nWorkers];
for (int w = 0; w < nWorkers; ++w) {
totShifts[w] = model.AddVar(0, GRB.INFINITY, 0, GRB.CONTINUOUS,
Workers[w] + "TotShifts");
}
GRBLinExpr lhs;
// Constraint: assign exactly shiftRequirements[s] workers
// to each shift s, plus the slack
for (int s = 0; s < nShifts; ++s) {
lhs = new GRBLinExpr();
lhs.AddTerm(1.0, slacks[s]);
for (int w = 0; w < nWorkers; ++w) {
lhs.AddTerm(1.0, x[w, s]);
}
model.AddConstr(lhs == shiftRequirements[s], Shifts[s]);
}
// Constraint: set totSlack equal to the total slack
lhs = new GRBLinExpr();
for (int s = 0; s < nShifts; ++s) {
lhs.AddTerm(1.0, slacks[s]);
}
model.AddConstr(lhs == totSlack, "totSlack");
// Constraint: compute the total number of shifts for each worker
for (int w = 0; w < nWorkers; ++w) {
lhs = new GRBLinExpr();
for (int s = 0; s < nShifts; ++s) {
lhs.AddTerm(1.0, x[w, s]);
}
model.AddConstr(lhs == totShifts[w], "totShifts" + Workers[w]);
}
// Objective: minimize the total slack
model.SetObjective(1.0*totSlack);
// Optimize
int status = solveAndPrint(model, totSlack, nWorkers, Workers, totShifts);
if (status != GRB.Status.OPTIMAL) {
return;
}
// Constrain the slack by setting its upper and lower bounds
totSlack.UB = totSlack.X;
totSlack.LB = totSlack.X;
// Variable to count the average number of shifts worked
GRBVar avgShifts =
model.AddVar(0, GRB.INFINITY, 0, GRB.CONTINUOUS, "avgShifts");
// Variables to count the difference from average for each worker;
// note that these variables can take negative values.
GRBVar[] diffShifts = new GRBVar[nWorkers];
for (int w = 0; w < nWorkers; ++w) {
diffShifts[w] = model.AddVar(-GRB.INFINITY, GRB.INFINITY, 0,
GRB.CONTINUOUS, Workers[w] + "Diff");
}
// Constraint: compute the average number of shifts worked
lhs = new GRBLinExpr();
for (int w = 0; w < nWorkers; ++w) {
lhs.AddTerm(1.0, totShifts[w]);
}
model.AddConstr(lhs == nWorkers * avgShifts, "avgShifts");
// Constraint: compute the difference from the average number of shifts
for (int w = 0; w < nWorkers; ++w) {
model.AddConstr(totShifts[w] - avgShifts == diffShifts[w],
Workers[w] + "Diff");
}
// Objective: minimize the sum of the square of the difference from the
// average number of shifts worked
GRBQuadExpr qobj = new GRBQuadExpr();
for (int w = 0; w < nWorkers; ++w) {
qobj.AddTerm(1.0, diffShifts[w], diffShifts[w]);
}
model.SetObjective(qobj);
// Optimize
status = solveAndPrint(model, totSlack, nWorkers, Workers, totShifts);
if (status != GRB.Status.OPTIMAL) {
return;
}
// Dispose of model and env
model.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " +
e.Message);
}
}
private static int solveAndPrint(GRBModel model, GRBVar totSlack,
int nWorkers, String[] Workers,
GRBVar[] totShifts)
{
model.Optimize();
int status = model.Status;
if ((status == GRB.Status.INF_OR_UNBD) ||
(status == GRB.Status.INFEASIBLE) ||
(status == GRB.Status.UNBOUNDED)) {
Console.WriteLine("The model cannot be solved "
+ "because it is infeasible or unbounded");
return status;
}
if (status != GRB.Status.OPTIMAL) {
Console.WriteLine("Optimization was stopped with status " + status);
return status;
}
// Print total slack and the number of shifts worked for each worker
Console.WriteLine("\nTotal slack required: " + totSlack.X);
for (int w = 0; w < nWorkers; ++w) {
Console.WriteLine(Workers[w] + " worked " +
totShifts[w].X + " shifts");
}
Console.WriteLine("\n");
return status;
}
}
