// Copyright 2025, Gurobi Optimization, LLC// A simple sensitivity analysis example which reads a MIP model from a// file and solves it. Then uses the scenario feature to analyze the impact// w.r.t. the objective function of each binary variable if it is set to// 1-X, where X is its value in the optimal solution.//// Usage://     java Sensitivity <model filename>importcom.gurobi.gurobi.*;publicclassSensitivity{// Maximum number of scenarios to be consideredprivatestaticfinalintMAXSCENARIOS=100;publicstaticvoidmain(String[]args){if(args.length<1){System.out.println("Usage: java Sensitivity filename");System.exit(1);}try{// Create environmentGRBEnvenv=newGRBEnv();// Read modelGRBModelmodel=newGRBModel(env,args[0]);intscenarios;if(model.get(GRB.IntAttr.IsMIP)==0){System.out.println("Model is not a MIP");System.exit(1);}// Solve modelmodel.optimize();if(model.get(GRB.IntAttr.Status)!=GRB.OPTIMAL){System.out.println("Optimization ended with status "+model.get(GRB.IntAttr.Status));System.exit(1);}// Store the optimal solutiondoubleorigObjVal=model.get(GRB.DoubleAttr.ObjVal);GRBVar[]vars=model.getVars();double[]origX=model.get(GRB.DoubleAttr.X,vars);scenarios=0;// Count number of unfixed, binary variables in model. For each we// create a scenario.for(inti=0;i<vars.length;i++){GRBVarv=vars[i];charvType=v.get(GRB.CharAttr.VType);if(v.get(GRB.DoubleAttr.LB)==0&&v.get(GRB.DoubleAttr.UB)==1&&(vType==GRB.BINARY||vType==GRB.INTEGER)){scenarios++;if(scenarios>=MAXSCENARIOS)break;}}System.out.println("###  construct multi-scenario model with "+scenarios+" scenarios");// Set the number of scenarios in the model */model.set(GRB.IntAttr.NumScenarios,scenarios);scenarios=0;// Create a (single) scenario model by iterating through unfixed// binary variables in the model and create for each of these// variables a scenario by fixing the variable to 1-X, where X is its// value in the computed optimal solutionfor(inti=0;i<vars.length;i++){GRBVarv=vars[i];charvType=v.get(GRB.CharAttr.VType);if(v.get(GRB.DoubleAttr.LB)==0&&v.get(GRB.DoubleAttr.UB)==1&&(vType==GRB.BINARY||vType==GRB.INTEGER)&&scenarios<MAXSCENARIOS){// Set ScenarioNumber parameter to select the corresponding// scenario for adjustmentsmodel.set(GRB.IntParam.ScenarioNumber,scenarios);// Set variable to 1-X, where X is its value in the optimal solution */if(origX[i]<0.5)v.set(GRB.DoubleAttr.ScenNLB,1.0);elsev.set(GRB.DoubleAttr.ScenNUB,0.0);scenarios++;}else{// Add MIP start for all other variables using the optimal// solution of the base modelv.set(GRB.DoubleAttr.Start,origX[i]);}}// Solve multi-scenario modelmodel.optimize();// In case we solved the scenario model to optimality capture the// sensitivity informationif(model.get(GRB.IntAttr.Status)==GRB.OPTIMAL){// get the model sense (minimization or maximization)intmodelSense=model.get(GRB.IntAttr.ModelSense);scenarios=0;for(inti=0;i<vars.length;i++){GRBVarv=vars[i];charvType=v.get(GRB.CharAttr.VType);if(v.get(GRB.DoubleAttr.LB)==0&&v.get(GRB.DoubleAttr.UB)==1&&(vType==GRB.BINARY||vType==GRB.INTEGER)){// Set scenario parameter to collect the objective value of the// corresponding scenariomodel.set(GRB.IntParam.ScenarioNumber,scenarios);// Collect objective value and bound for the scenariodoublescenarioObjVal=model.get(GRB.DoubleAttr.ScenNObjVal);doublescenarioObjBound=model.get(GRB.DoubleAttr.ScenNObjBound);System.out.print("Objective sensitivity for variable "+v.get(GRB.StringAttr.VarName)+" is ");// Check if we found a feasible solution for this scenarioif(modelSense*scenarioObjVal>=GRB.INFINITY){// Check if the scenario is infeasibleif(modelSense*scenarioObjBound>=GRB.INFINITY)System.out.println("infeasible");elseSystem.out.println("unknown (no solution available)");}else{// Scenario is feasible and a solution is availableSystem.out.println(""+modelSense*(scenarioObjVal-origObjVal));}scenarios++;if(scenarios>=MAXSCENARIOS)break;}}}// Dispose of model and environmentmodel.dispose();env.dispose();}catch(GRBExceptione){System.out.println("Error code: "+e.getErrorCode());System.out.println(e.getMessage());e.printStackTrace();}}}