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workforce3_c++.cpp
/* Copyright 2022, Gurobi Optimization, LLC */ /* Assign workers to shifts; each worker may or may not be available on a particular day. If the problem cannot be solved, relax the model to determine which constraints cannot be satisfied, and how much they need to be relaxed. */ #include "gurobi_c++.h" #include <sstream> using namespace std; int main(int argc, char *argv[]) { GRBEnv* env = 0; GRBConstr* c = 0; GRBVar** x = 0; GRBVar* vars = 0; int xCt = 0; try { // Sample data const int nShifts = 14; const int nWorkers = 7; // Sets of days and workers string Shifts[] = { "Mon1", "Tue2", "Wed3", "Thu4", "Fri5", "Sat6", "Sun7", "Mon8", "Tue9", "Wed10", "Thu11", "Fri12", "Sat13", "Sun14" }; string Workers[] = { "Amy", "Bob", "Cathy", "Dan", "Ed", "Fred", "Gu" }; // Number of workers required for each shift double shiftRequirements[] = { 3, 2, 4, 4, 5, 6, 5, 2, 2, 3, 4, 6, 7, 5 }; // Amount each worker is paid to work one shift double pay[] = { 10, 12, 10, 8, 8, 9, 11 }; // Worker availability: 0 if the worker is unavailable for a shift double availability[][nShifts] = { { 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 env = new GRBEnv(); GRBModel model = GRBModel(*env); model.set(GRB_StringAttr_ModelName, "assignment"); // Assignment variables: x[w][s] == 1 if worker w is assigned // to shift s. Since an assignment model always produces integer // solutions, we use continuous variables and solve as an LP. x = new GRBVar*[nWorkers]; for (int w = 0; w < nWorkers; ++w) { x[w] = model.addVars(nShifts); xCt++; for (int s = 0; s < nShifts; ++s) { ostringstream vname; vname << Workers[w] << "." << Shifts[s]; x[w][s].set(GRB_DoubleAttr_UB, availability[w][s]); x[w][s].set(GRB_DoubleAttr_Obj, pay[w]); x[w][s].set(GRB_StringAttr_VarName, vname.str()); } } // The objective is to minimize the total pay costs model.set(GRB_IntAttr_ModelSense, GRB_MINIMIZE); // Constraint: assign exactly shiftRequirements[s] workers // to each shift s for (int s = 0; s < nShifts; ++s) { GRBLinExpr lhs = 0; for (int w = 0; w < nWorkers; ++w) { lhs += x[w][s]; } model.addConstr(lhs == shiftRequirements[s], Shifts[s]); } // Optimize model.optimize(); int status = model.get(GRB_IntAttr_Status); if (status == GRB_UNBOUNDED) { cout << "The model cannot be solved " << "because it is unbounded" << endl; return 1; } if (status == GRB_OPTIMAL) { cout << "The optimal objective is " << model.get(GRB_DoubleAttr_ObjVal) << endl; return 0; } if ((status != GRB_INF_OR_UNBD) && (status != GRB_INFEASIBLE)) { cout << "Optimization was stopped with status " << status << endl; return 1; } // Relax the constraints to make the model feasible cout << "The model is infeasible; relaxing the constraints" << endl; int orignumvars = model.get(GRB_IntAttr_NumVars); model.feasRelax(0, false, false, true); model.optimize(); status = model.get(GRB_IntAttr_Status); if ((status == GRB_INF_OR_UNBD) || (status == GRB_INFEASIBLE) || (status == GRB_UNBOUNDED)) { cout << "The relaxed model cannot be solved " << "because it is infeasible or unbounded" << endl; return 1; } if (status != GRB_OPTIMAL) { cout << "Optimization was stopped with status " << status << endl; return 1; } cout << "\nSlack values:" << endl; vars = model.getVars(); for (int i = orignumvars; i < model.get(GRB_IntAttr_NumVars); ++i) { GRBVar sv = vars[i]; if (sv.get(GRB_DoubleAttr_X) > 1e-6) { cout << sv.get(GRB_StringAttr_VarName) << " = " << sv.get(GRB_DoubleAttr_X) << endl; } } } catch (GRBException e) { cout << "Error code = " << e.getErrorCode() << endl; cout << e.getMessage() << endl; } catch (...) { cout << "Exception during optimization" << endl; } delete[] c; for (int i = 0; i < xCt; ++i) { delete[] x[i]; } delete[] x; delete[] vars; delete env; return 0; }