https://github.com/aquemy/zenosolver
Optimal solver for multiobjectives MultiZenoTravel problems.
https://github.com/aquemy/zenosolver
c-plus-plus-14 multiobjective-optimization research-project
Last synced: 3 months ago
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Optimal solver for multiobjectives MultiZenoTravel problems.
- Host: GitHub
- URL: https://github.com/aquemy/zenosolver
- Owner: aquemy
- Created: 2014-01-15T11:24:10.000Z (about 12 years ago)
- Default Branch: master
- Last Pushed: 2017-07-21T09:20:06.000Z (over 8 years ago)
- Last Synced: 2025-01-23T18:25:11.393Z (about 1 year ago)
- Topics: c-plus-plus-14, multiobjective-optimization, research-project
- Language: C++
- Homepage:
- Size: 861 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
ZenoSolver
==========
Optimal solver for multiobjectives ZenoTransportation problem.
# Requirements
CMake
g++ >= 4.7 for C++11 features.
(optional) doxygen for documentation
# How to compile
mkdir build && cd build
cmake ..
make -j
# Build & Compilation Options
By default the build is in Release mode, with all optimisations.
To activate the DEBUG build, in build folder, use:
cmake .. -DCMAKE_BUILD_TYPE=DEBUG
make
# RunTime Options
As ZenoSolver handles only integers for cost and durations, it will cast generated vectors (or provided data) to integers. The adjustement factor (option -r) is a multiplicative constant in order to avoid some errors (for instance, obtaining more than once the value 0 because log(i) and log(i+1) have same floor value.
By default it is set to 1 but a better value for most of functions could be 100.
More information using ./zenoSolver -h.
# References
- **True Pareto Fronts for Multi-Objective AI Planning Instances**. *Alexandre Quemy, Marc Schoenauer.* Francesco Chicano and Gabriela Ochoa. European Conference on Combinatorial Optimization - EvoCOP, Apr 2015, Copenhague, Denmark. LNCS 9026, Springer Verlag, pp.197-208, 2015.
- **Solving Large MultiZenoTravel Benchmarks with Divide-and-Evolve.** *Alexandre Quemy, Marc Schoenauer, Vincent Vidal, Johann Dréo, Pierre Savéant.* Learning and Intelligent OptimizatioN - LION 9, Jan 2015, Lille, France. LNCS 8994, Springer Verlag, pp.262-267, 2015.