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ParadisEO-MO: From Fitness Landscape Analysis to Efficient Local Search Algorithms

Abstract : This document presents a general-purpose software framework dedicated to the design, the analysis and the implementation of local search algorithms: ParadisEO-MO. A substantial number of single-solution based local search metaheuristics has been proposed so far, and an attempt of unifying existing approaches is here presented. Based on a fine-grained decomposition, a conceptual model is proposed and is validated by regarding a number of state-of-the-art methodologies as simple variants of the same structure. This model is then incorporated into the ParadisEO-MO software framework. This framework has proven its efficiency and high flexibility by enabling the resolution of many academic and real-world optimization problems from science and industry.
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Contributor : Arnaud Liefooghe Connect in order to contact the contributor
Submitted on : Tuesday, June 4, 2013 - 3:29:47 PM
Last modification on : Thursday, January 20, 2022 - 5:32:29 PM
Long-term archiving on: : Thursday, September 5, 2013 - 4:23:28 AM


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  • HAL Id : hal-00665421, version 2


Jérémie Humeau, Arnaud Liefooghe, El-Ghazali Talbi, Sébastien Verel. ParadisEO-MO: From Fitness Landscape Analysis to Efficient Local Search Algorithms. [Research Report] RR-7871, INRIA. 2013. ⟨hal-00665421v2⟩



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