Article ID: | iaor20108319 |
Volume: | 209 |
Issue: | 2 |
Start Page Number: | 104 |
End Page Number: | 112 |
Publication Date: | Mar 2011 |
Journal: | European Journal of Operational Research |
Authors: | Talbi El-Ghazali, Jourdan Laetitia, Liefooghe Arnaud |
Keywords: | decomposition |
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.