EMOC stands for Evolutionary Multi-objective Optimization in C++ which is a framework for single-objective and multi-objective optimization.
For more information about installation and usage, please refer to the document site.
Features #
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Rich algorithms and problems
EMOC implemented about 30 algorithms and more than 80 test problems which both include single-objective and multi-objective types.
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Developed in C++ and Cross-platform
All the source code of EMOC are wrote in C++. So the running efficiency is guaranteed when comparing other implementation with python, java or matlab. We also provide cross-platform compatibility for users with different operator systems.
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Friendly GUI
EMOC provides a user-friendly GUI with the function of configuring parameters of once-run and experiments without writing a single line of code.
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Various Optimization Types
EMOC supports unconstraint optimization, constraint optimization and combinatorial optimization (including binary encoding and permutation encoding).
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Save into Excel or Latex
Users can save the experiment results of EMOC in the format of Latex.