The following examples showcase how to use the different Operations Research libraries.

• Constraint Solver examples:

  • cryptarithm.cc Demonstrates the use of basic modeling objects (integer variables, arithmetic constraints and expressions, simple search).
  • golomb.cc Demonstrates how to handle objective functions and collect solutions found during the search.
  • magic_square.cc Shows how to use the automatic search to solve your problem.
  • costas_array.cc Solves the problem of Costas Array (a constrained assignment problem used for radars) with two version. On version is a feasibility version with hard constraints, the other version is an optimization version with soft constraints and violation costs.
  • jobshop.cc Demonstrates scheduling of jobs on different machines.
  • nqueens.cc Solves the n-queen problem. It also demonstrates how to break symmetries during search.
  • network_routing_sat.cc Solves a multicommodity mono-routing problem with capacity constraints and a max usage cost structure.
  • sports_scheduling_sat.cc Finds a soccer championship schedule. Its uses an original approach where all constraints attached to either one team, or one week are regrouped into one global 'AllowedAssignment' constraints.
  • dobble_ls.cc Shows how to write Local Search operators and Local Search filters in a context of an assignment/partitioning problem. It also shows how to write a simple constraint.

• Routing examples:

  • cvrptw.cc Capacitated Vehicle Routing Problem with Time Windows.
  • pdptw.cc Pickup and Delivery Problem with Time Windows.

• Graph examples:

  • flow_api.cc Demonstrates how to use Min-Cost Flow and Max-Flow api.
  • linear_assignment_api.cc Demonstrates how to use the Linear Sum Assignment solver.
  • dimacs_assignment.cc Solves DIMACS challenge on assignment problems.

• Linear and integer programming examples:

  • linear_programming.cc Demonstrates how to use the linear solver wrapper API to solve Linear Programming problems.
  • integer_programming.cc Demonstrates how to use the linear solver wrapper API to solve Integer Programming problems.
  • linear_solver_protocol_buffers.cc Demonstrates how protocol buffers can be used as input and output to the linear solver wrapper.
  • strawberry_fields_with_column_generation.cc Complex example that demonstrates how to use dynamic column generation to solve a 2D covering problem.

Running the examples will involve building them, then running them.
You can run the following command from the top directory:

make build SOURCE=examples/cpp/<example>.cc
make run SOURCE=examples/cpp/<example>.cc