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workforce2.m
function workforce2() % Copyright 2024, 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, use IIS iteratively to % find all conflicting constraints. % define data nShifts = 14; nWorkers = 7; nVars = nShifts * nWorkers; Shifts = {'Mon1'; 'Tue2'; 'Wed3'; 'Thu4'; 'Fri5'; 'Sat6'; 'Sun7'; 'Mon8'; 'Tue9'; 'Wed10'; 'Thu11'; 'Fri12'; 'Sat13'; 'Sun14'}; Workers = {'Amy'; 'Bob'; 'Cathy'; 'Dan'; 'Ed'; 'Fred'; 'Gu'}; pay = [10; 12; 10; 8; 8; 9; 11]; shiftRequirements = [3; 2; 4; 4; 5; 6; 5; 2; 2; 3; 4; 6; 7; 5]; availability = [ 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 ]; % Build model model.modelname = 'workforce2'; model.modelsense = 'min'; % Initialize assignment decision 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. model.ub = ones(nVars, 1); model.obj = zeros(nVars, 1); for w = 1:nWorkers for s = 1:nShifts model.varnames{s+(w-1)*nShifts} = sprintf('%s.%s', Workers{w}, Shifts{s}); model.obj(s+(w-1)*nShifts) = pay(w); if availability(w, s) == 0 model.ub(s+(w-1)*nShifts) = 0; end end end % Set-up shift-requirements constraints model.sense = repmat('=', nShifts, 1); model.rhs = shiftRequirements; model.constrnames = Shifts; model.A = sparse(nShifts, nVars); for s = 1:nShifts for w = 1:nWorkers model.A(s, s+(w-1)*nShifts) = 1; end end % Save model gurobi_write(model, 'workforce2_m.lp'); % Optimize params.logfile = 'workforce2_m.log'; result = gurobi(model, params); % If infeasible, remove IIS rows until it becomes feasible numremoved = 0; if strcmp(result.status, 'INFEASIBLE') numremoved = 0; while strcmp(result.status, 'INFEASIBLE') iis = gurobi_iis(model, params); keep = find(~iis.Arows); fprintf('Removing rows: '); disp(model.constrnames{iis.Arows}) model.A = model.A(keep, :); model.sense = model.sense(keep, :); model.rhs = model.rhs(keep, :); model.constrnames = model.constrnames(keep,:); numremoved = numremoved + 1; result = gurobi(model, params); end end % Display results if strcmp(result.status, 'OPTIMAL') if numremoved > 0 fprintf('It becomes feasible after %d rounds of IIS row removing\n', numremoved); end printsolution(result, Shifts, Workers) else % Just to handle user interruptions or other problems fprintf('Unexpected status %s\n',result.status) end end function printsolution(result, Shifts, Workers) % Helper function to display results nShifts = length(Shifts); nWorkers = length(Workers); fprintf('The optimal objective is %g\n', result.objval); fprintf('Schedule:\n'); for s = 1:nShifts fprintf('\t%s:', Shifts{s}); for w = 1:nWorkers if result.x(s+(w-1)*nShifts) > 0.9 fprintf('%s ', Workers{w}); end end fprintf('\n'); end end