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A Unified Model for Evolutionary Multiobjective Optimization and its Implementation in a General Purpose Software Framework: ParadisEO-MOEO

Arnaud Liefooghe 1, 2, * Laetitia Jourdan 1, 2 El-Ghazali Talbi 1, 2
* Corresponding author
2 DOLPHIN - Parallel Cooperative Multi-criteria Optimization
Inria Lille - Nord Europe, LIFL - Laboratoire d'Informatique Fondamentale de Lille
Abstract : This paper gives a concise overview of evolutionary algorithms for multiobjective optimization. A substantial number of evolutionary computation methods for multiobjective problem solving has been proposed so far, and an attempt of unifying existing approaches is here presented. Based on a fine-grained decomposition and following the main issues of fitness assignment, diversity preservation and elitism, a conceptual global model is proposed and is validated by regarding a number of state-of-the-art algorithms as simple variants of the same structure. The presented model is then incorporated into a general-purpose software framework dedicated to the design and the implementation of evolutionary multiobjective optimization techniques: ParadisEO-MOEO. This package has proven its validity and flexibility by enabling the resolution of many real-world and hard multiobjective optimization problems.
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Submitted on : Monday, April 20, 2009 - 11:17:29 AM
Last modification on : Thursday, January 20, 2022 - 5:27:49 PM
Long-term archiving on: : Thursday, June 10, 2010 - 6:41:37 PM

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  • HAL Id : inria-00376770, version 1
  • ARXIV : 0904.2987

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Arnaud Liefooghe, Laetitia Jourdan, El-Ghazali Talbi. A Unified Model for Evolutionary Multiobjective Optimization and its Implementation in a General Purpose Software Framework: ParadisEO-MOEO. [Research Report] RR-6906, INRIA. 2009. ⟨inria-00376770⟩

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