C++ examples

These examples in C++ use the Concert Technology C++ API of CPLEX .

The following examples are delivered with CPLEX.

benders.cpp demonstrates a Benders decomposition.

ilobendersatsp.cpp demonstrates legacy lazy constraint callbacks to separate integer feasible LP solutions and legacy user cut callbacks to separate fractional infeasible LP solutions in a do-it-yourself Benders decomposition of an asymmetric traveling salesperson problem.

ilobendersatsp2.cpp demonstrates generic callbacks to separate integer feasible LP solutions in a context of lazy constraints as well as generic callbacks to separate fractional infeasible LP solutions in a context of user cuts, all in a do-it-yourself Benders decomposition of an asymmetric traveling salesperson problem.

blend.cpp is a blending problem.

cutstock.cpp is a cutting-stock model illustrating column generation.

iloconflictex1.cpp demonstrates how to use the conflict refiner.

etsp.cpp is a scheduling problem with costs for earliness and for tardiness.

facility.cpp is a warehouse-location problem. Optionally, the example can apply a Benders decomposition.

fixcost1.cpp is a production planning problem with fixed costs.

ilofixnet.cpp uses indicator constraints to avoid numeric difficulty in a fixed-charge network flow problem.

foodmanufact.cpp implements a solution to the food production planning problem, well known from the modeling textbook of H. P. Williams.

ilogenericbranch.cpp demonstrates how to perform customized branching using the generic callback.

iloadmipex1.cpp uses node and branch callbacks to optimize a MIP.

iloadmipex2.cpp uses a heuristic callback to optimize a MIP.

iloadmipex3.cpp uses a branch callback on a MIP with special ordered sets (SOS).

iloadmipex4.cpp demonstrates how to add lazy constraints and user cuts.

iloadmipex5.cpp adds cuts through the cut callback for a MIP.

iloadmipex6.cpp starts a MIP optimization from an LP solution.

iloadmipex8.cpp demonstrates how to add lazy constraints and user cuts with the generic callback.

iloadmipex9.cpp uses a generic callback invoking a heuristic.

ilodiet.cpp is a linear program that can be generated by columns (add foods to the diet) or by rows (add requirements to the diet); optionally, demonstrates how to model a multiobjective problem by creating a second objective.

ilomultiobjex1.cpp demonstrates how to read in and optimize a multiobjective problem.

ilogoalex1.cpp uses the goal API to branch.

ilogoalex2.cpp uses the goal API to add cuts.

ilogoalex3.cpp uses the goal API to add node evaluators; it derives from ilogoalex1.cpp.

ilolpex1.cpp is equivalent to lpex1.c; it shows how to populate data in a model.

ilolpex2.cpp is equivalent to lpex2.c; it shows how to add data from a file.

ilolpex3.cpp is equivalent to lpex3.c; it shows how to add rows to a model and re-optimize.

ilolpex4.cpp is equivalent to lpex4.c; it illustrates callbacks.

ilolpex6.cpp is equivalent to lpex6.c; it shows how to load a basis.

ilolpex7.cpp is equivalent to lpex7.c; it shows how to access names of columns.

ilomipex1.cpp is equivalent to mipex1.c; it is a basic MIP.

ilomipex2.cpp is equivalent to mipex2.c; another basic MIP with data from files.

ilomipex3.cpp is equivalent to mipex3.c; it demonstrates special ordered sets (SOSs) and priorities.

ilomipex4.cpp demonstrates how to use an aborter to interrupt optimization and how to use informational callbacks for logging, timing, or setting a node limit.

ilomiqpex1.cpp is equivalent to miqpex1.c (quadratic objective in MIP).

iloqpex1.cpp is equivalent to qpex1.c (quadratic objective).

iloqpex2.cpp is equivalent to qpex2.c (quadratic objective with data read from a file).

iloqpex3.cpp uses the Concert Technology interface for quadratic expressions to enter and to modify a model with quadratic expressions in linear combination in the objective function.

iloindefqpex1.cpp enters and solves an indefinite quadratic program (nonPSD QP) to a local optimum.

iloqcpex1.cpp solves a quadratically constrained problem.

ilopopulate.cpp shows how to generate and store multiple solutions in the solution pool.

ilosocpex1.cpp shows how to access dual values and reduced costs in SOCP models.

iloqcpdual.cpp shows how to access dual values and reduced costs in quadratically constrained programming models (QCP).

iloglobalqpex1.cpp shows how to read a convex or nonconvex quadratic programming model (QP) or mixed integer quadratic programming model (MIQP) and solve it for a first order or global optimum.

ilotuneset.cpp analyzes a set of models and suggests nondefault parameter settings for better performance.

inout1.cpp is a production model.

inout3.cpp is another production model.

mixblend.cpp is a blending problem with integer variables.

rates.cpp is a planning problem with semi-continuous variables.

ilosteel.cpp is equivalent to rowsteel.c, steeldrv.c, steelsub.c; it solves the model known as steelT.mod in the AMPL book by Fourer, Gay, and Kernighan.

ilotransport.cpp uses a piecewise linear cost function.

warehouse.cpp is a warehouse-assignment problem using goals.