Metadata-Version: 1.1
Name: evoalgos
Version: 0.5
Summary: Modular evolutionary algorithms
Home-page: https://ls11-www.cs.tu-dortmund.de/people/swessing/evoalgos/doc/
Author: Simon Wessing
Author-email: simon.wessing@tu-dortmund.de
License: BSD
Description: Description
        ===========
        
        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 are provided. The algorithms can
        work on real-valued and binary search spaces.
        
        The package is geared to work with optimization problems as defined in the
        package optproblems. The whole package assumes minimization problems
        throughout!
        
        Documentation
        =============
        
        The documentation is located at
        https://ls11-www.cs.tu-dortmund.de/people/swessing/evoalgos/doc/
        
Keywords: evolutionary optimization algorithm multiobjective EMOA MOEA SMS SBX NSGA2 hypervolume self-adaptive evolution strategy nearest-better
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Requires: optproblems
