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Workforce5.java
/* Copyright 2023, Gurobi Optimization, LLC */
/* Assign workers to shifts; each worker may or may not be available on a
particular day. We use multi-objective optimization to solve the model.
The highest-priority objective minimizes the sum of the slacks
(i.e., the total number of uncovered shifts). The secondary objective
minimizes the difference between the maximum and minimum number of
shifts worked among all workers. The second optimization is allowed
to degrade the first objective by up to the smaller value of 10% and 2 */
import gurobi.*;
public class Workforce5 {
public static void main(String[] args) {
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", "Tobi" };
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 },
{ 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1 },
{ 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 } };
// Create environment
GRBEnv env = new GRBEnv();
// Create initial model
GRBModel model = new GRBModel(env);
model.set(GRB.StringAttr.ModelName, "Workforce5");
// Initialize assignment decision 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, GRB.EQUAL, shiftRequirements[s], Shifts[s]);
}
// Constraint: set totSlack equal to the total slack
lhs = new GRBLinExpr();
lhs.addTerm(-1.0, totSlack);
for (int s = 0; s < nShifts; ++s) {
lhs.addTerm(1.0, slacks[s]);
}
model.addConstr(lhs, GRB.EQUAL, 0, "totSlack");
// Constraint: compute the total number of shifts for each worker
for (int w = 0; w < nWorkers; ++w) {
lhs = new GRBLinExpr();
lhs.addTerm(-1.0, totShifts[w]);
for (int s = 0; s < nShifts; ++s) {
lhs.addTerm(1.0, x[w][s]);
}
model.addConstr(lhs, GRB.EQUAL, 0, "totShifts" + Workers[w]);
}
// Constraint: set minShift/maxShift variable to less <=/>= to the
// number of shifts among all workers
GRBVar minShift = model.addVar(0, GRB.INFINITY, 0, GRB.CONTINUOUS,
"minShift");
GRBVar maxShift = model.addVar(0, GRB.INFINITY, 0, GRB.CONTINUOUS,
"maxShift");
model.addGenConstrMin(minShift, totShifts, GRB.INFINITY, "minShift");
model.addGenConstrMax(maxShift, totShifts, -GRB.INFINITY, "maxShift");
// Set global sense for ALL objectives
model.set(GRB.IntAttr.ModelSense, GRB.MINIMIZE);
// Set primary objective
GRBLinExpr obj0 = new GRBLinExpr();
obj0.addTerm(1.0, totSlack);
model.setObjectiveN(obj0, 0, 2, 1.0, 2.0, 0.1, "TotalSlack");
// Set secondary objective
GRBLinExpr obj1 = new GRBLinExpr();
obj1.addTerm(1.0, maxShift);
obj1.addTerm(-1.0, minShift);
model.setObjectiveN(obj1, 1, 1, 1.0, 0.0, 0.0, "Fairness");
// Save problem
model.write("Workforce5.lp");
// Optimize
int status = solveAndPrint(model, totSlack, nWorkers, Workers, totShifts);
if (status != GRB.OPTIMAL)
return;
// Dispose of model and environment
model.dispose();
env.dispose();
} catch (GRBException e) {
System.out.println("Error code: " + e.getErrorCode() + ". " +
e.getMessage());
}
}
private static int solveAndPrint(GRBModel model, GRBVar totSlack,
int nWorkers, String[] Workers,
GRBVar[] totShifts) throws GRBException {
model.optimize();
int status = model.get(GRB.IntAttr.Status);
if (status == GRB.Status.INF_OR_UNBD ||
status == GRB.Status.INFEASIBLE ||
status == GRB.Status.UNBOUNDED ) {
System.out.println("The model cannot be solved "
+ "because it is infeasible or unbounded");
return status;
}
if (status != GRB.Status.OPTIMAL ) {
System.out.println("Optimization was stopped with status " + status);
return status;
}
// Print total slack and the number of shifts worked for each worker
System.out.println("\nTotal slack required: " +
totSlack.get(GRB.DoubleAttr.X));
for (int w = 0; w < nWorkers; ++w) {
System.out.println(Workers[w] + " worked " +
totShifts[w].get(GRB.DoubleAttr.X) + " shifts");
}
System.out.println("\n");
return status;
}
}
