Modular evolutionary algorithms
This package contains the S-metric selection evolutionary multi-objective optimization algorithm (SMS-EMOA) and the non-dominated sorting genetic algorithm 2 (NSGA2) for multiobjective optimization. For single-objective optimization, classical evolution strategies and the rather unknown CMSA-ES (covariance matrix self-adaptation evolution strategy) are provided. Variation for real-valued and binary search spaces is included and new variation operators can be easily added thanks to the modular concept.
The package is geared to work with optimization problems as defined in the package optproblems. The whole package assumes minimization problems throughout!
The documentation is located at https://ls11-www.cs.tu-dortmund.de/people/swessing/evoalgos/doc/