A software framework based on a conceptual unified model for evolutionary multiobjective optimization: ParadisEO-MOEO

This paper presents a general-purpose software framework dedicated to the design and the implementation of evolutionary multiobjective optimization techniques: ParadisEO-MOEO. A concise overview of evolutionary algorithms for multiobjective optimization is given. A substantial number of methods has...

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Bibliographic Details
Published in:European journal of operational research 2011-03, Vol.209 (2), p.104-112
Main Authors: Liefooghe, Arnaud, Jourdan, Laetitia, Talbi, El-Ghazali
Format: Article
Language:English
Subjects:
Algorithm design and implementation
Algorithms
Applied sciences
Computer Science
Conceptual unified model
Decision theory. Utility theory
Evolutionary algorithms
Exact sciences and technology
Genetic algorithms
Mathematical models
Mathematical programming
Multiple objective programming
Multiple objective programming Evolutionary algorithms Conceptual unified model Algorithm design and implementation Software framework
Operational research and scientific management
Operational research. Management science
Operations Research
Optimization techniques
Software
Software framework
Studies
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Summary:This paper presents a general-purpose software framework dedicated to the design and the implementation of evolutionary multiobjective optimization techniques: ParadisEO-MOEO. A concise overview of evolutionary algorithms for multiobjective optimization is given. A substantial number of methods has been proposed so far, and an attempt of conceptually unifying existing approaches is presented here. Based on a fine-grained decomposition and following the main issues of fitness assignment, diversity preservation and elitism, a conceptual model is proposed and is validated by regarding a number of state-of-the-art algorithms as simple variants of the same structure. This model is then incorporated into the ParadisEO-MOEO software framework. This framework has proven its validity and high flexibility by enabling the resolution of many academic, real-world and hard multiobjective optimization problems.
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2010.07.023