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<summary> C++ examples to demonstrate usage of the different
Operations Research libraries. </summary>
- 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.
- jobshop_ls.cc Demonstrates scheduling of jobs on different machines with
a search using Local Search and Large Neighorhood Search.
- nqueens.cc Solves the n-queen problem. It also demonstrates how to break
symmetries during search.
- network_routing.cc Solves a multicommodity mono-routing
problem with capacity constraints and a max usage cost structure.
- sports_scheduling.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:
- tsp.cc Travelling Salesman Problem.
- 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.
- Utilities
- model_util.cc A utility to manipulate model files (.cp) dumped by the
solver.

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# C++ examples
The following examples showcase how to use the different Operations Research libraries.
## Examples list
- 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.
- jobshop_ls.cc Demonstrates scheduling of jobs on different machines with
a search using Local Search and Large Neighorhood Search.
- nqueens.cc Solves the n-queen problem. It also demonstrates how to break
symmetries during search.
- network_routing.cc Solves a multicommodity mono-routing
problem with capacity constraints and a max usage cost structure.
- sports_scheduling.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:
- tsp.cc Travelling Salesman Problem.
- 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.
- Utilities
- model_util.cc A utility to manipulate model files (.cp) dumped by the
solver.
# Execution
Running the examples will involve building them, then running them.
You can run the following command from the **top** directory:
```shell
make build SOURCE=examples/cpp/<example>.cc
make run SOURCE=examples/cpp/<example>.cc
```

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Wherever you have or-tools installed, be sure to `PackageReference` the `Google.OrTools`
from the project file.
## Execution
# Execution
Running the examples will involve building them, then running them.
You can run the following command:
```shell
dotnet build examples/dotnet/<example>.csproj
dotnet run --no-build --project examples/dotnet/<example>.csproj
dotnet build <example>.csproj
dotnet run --no-build --project <example>.csproj
```
# Note on Google.OrTools.FSharp
@@ -34,7 +34,7 @@ Two input formats are allowed:
Running the examples will involve building them, then running them.
You can run the following command:
```shell
dotnet build examples/dotnet/<example>.fsproj
dotnet run --no-build --project examples/dotnet/<example>.fsproj
dotnet build <example>.fsproj
dotnet run --no-build --project <example>.fsproj
```

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# Java examples
The following examples showcase how to use the different Operations Research libraries.
# Execution
Running the examples will involve building them, then running them.
You can run the following command from the **top** directory:
```shell
make build SOURCE=examples/java/<example>.java
make run SOURCE=examples/java/<example>.java
```

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# Python examples
The following examples showcase how to use OrTools.
These examples should work for both Python2.7+ and Python3.5+.
We recommend that all projects you create target `Python 3.7`,
as this allows you to keep up-to-date with the latest Python frameworks.
Wherever you have `ortools` package installed, be sure to import it from your python file.
# Execution
For running the examples you can use the the following command:
```shell
python -m pip install --upgrade --user ortools
python <example>.py
```