swMATH ID: 34676
Software Authors: David Hadka
Description: Platypus is a framework for evolutionary computing in Python with a focus on multiobjective evolutionary algorithms (MOEAs). It differs from existing optimization libraries, including PyGMO, Inspyred, DEAP, and Scipy, by providing optimization algorithms and analysis tools for multiobjective optimization. It currently supports NSGA-II, NSGA-III, MOEA/D, IBEA, Epsilon-MOEA, SPEA2, GDE3, OMOPSO, SMPSO, and Epsilon-NSGA-II.
Homepage: http://platypus.readthedocs.org/en/latest/index.html
Related Software: Python; DEAP; PlatEMO; Geatpy; Scikit; NumPy; Matplotlib; MOEA; jMetal; Dask; PaGMO; jMetalPy; pymoo; GitHub; EGO; HeuristicLab; KEEL; Jenetics; gplearn; ECJ
Referenced in: 2 Publications

Referenced in 1 Serial

2 Journal of Global Optimization

Referencing Publications by Year