The MOEA Framework is a free and open source Java library for developing and experimenting with multiobjective evolutionary algorithms (MOEAs) and other general-purpose single and multiobjective optimization algorithms. The MOEA Framework supports genetic algorithms, differential evolution, particle swarm optimization, genetic programming, grammatical evolution, and more. A number of algorithms are provided out-of-the-box, including NSGA-II, NSGA-III, ε-MOEA, GDE3, PAES, PESA2, SPEA2, IBEA, SMS-EMOA, SMPSO, OMOPSO, CMA-ES, and MOEA/D. In addition, the MOEA Framework provides the tools necessary to rapidly design, develop, execute and statistically test optimization algorithms.
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References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Karsu, Özlem; Kara, Bahar Y.; Akkaya, Elif; Ozel, Aysu: Clean water network design for refugee camps (2021)
- Julian Blank, Kalyanmoy Deb: pymoo: Multi-objective Optimization in Python (2020) arXiv
- Benitez-Hidalgo, A.; Nebro, AJ; Garcia-Nieto, J.; Oregi, I.; Del Ser, J.: jMetalPy: a Python Framework for Multi-Objective Optimization with Metaheuristics (2019) arXiv
- Khoshkbarforoushha, Alireza; Khosravian, Alireza; Ranjan, Rajiv: Elasticity management of streaming data analytics flows on clouds (2017)