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ScenarioReductionSolver

ScenarioReductionSolver is a SMS++ module providing :Solver classes for the discrete scenario reduction problem: given a large set of weighted scenarios of a stochastic optimization problem, select a smaller representative subset that stays as close as possible, in the (weighted) Wasserstein sense, to the full distribution.

The Solvers read the scenario vectors directly from the DiscreteScenarioSet carried by a ScenarioReductionBlock, so they are independent of the concrete problem the scenarios describe and apply unchanged to any stochastic model.

  • ScenarioReductionSolver implements four heuristics selected at run time: Baseline selection by weight, Dupacova forward selection, and the BestFit and FirstFit local searches.
  • CSSCScenarioReductionSolver implements Cost-Space Scenario Clustering (CSSC) algorithm. It groups scenarios based on their impact on the objective value in the cost space, such that scenarios with similar cost-space distances are clustered together.

Getting started

These instructions will let you build the ScenarioReductionSolver module on your system.

Requirements

Build and install with CMake

Configure and build the library with:

mkdir build
cd build
cmake ..
cmake --build .

The library has the same configuration options of SMS++.

Optionally, install the library in the system with:

cmake --install .

Usage with CMake

After the library is built, you can use it in your CMake project with:

find_package(ScenarioReductionSolver)
target_link_libraries(<my_target> SMS++::ScenarioReductionSolver)

Build and install with makefiles

Carefully hand-crafted makefiles have also been developed for those unwilling to use CMake. Makefiles build the executable in-source (in the same directory tree where the code is) as opposed to out-of-source (in the copy of the directory tree constructed in the build/ folder) and therefore it is more convenient when having to recompile often, such as when developing/debugging a new module, as opposed to the compile-and-forget usage envisioned by CMake.

Each executable using ScenarioReductionSolver has to include a "main makefile" of the module, which typically is either makefile-c including all necessary libraries comprised the "core SMS++" one, or makefile-s including all necessary libraries but not the "core SMS++" one (for the common case in which this is used together with other modules that already include them). These in turn recursively include all the required other makefiles, hence one should only need to edit the "main makefile" for compilation type (C++ compiler and its options) and it all should be good to go. In case some of the external libraries are not at their default location, it should only be necessary to create the ../extlib/makefile-paths out of the extlib/makefile-default-paths-* for your OS * and edit the relevant bits (commenting out all the rest).

Check the SMS++ installation wiki for further details.

Getting help

If you need support, you want to submit bugs or propose a new feature, you can open a new issue.

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting merge requests to us.

Authors

Current Lead Authors

  • Minh Duc Pham
    Dipartimento di Informatica
    Università di Pisa

Contributors

License

This code is provided free of charge under the GNU Lesser General Public License version 3.0 - see the LICENSE file for details.

Disclaimer

The code is currently provided free of charge under an open-source license. As such, it is provided "as is", without any explicit or implicit warranty that it will properly behave or it will suit your needs. The Authors of the code cannot be considered liable, either directly or indirectly, for any damage or loss that anybody could suffer for having used it. More details about the non-warranty attached to this code are available in the license description file.

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SMS++ Solvers for discrete scenario reduction on stochastic optimization problems. | mirror of https://gitlab.com/smspp/scenarioreductionsolver

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