ParadisEO-MOEO: A Software Framework for Evolutionary Multi-Objective Optimization

Arnaud Liefooghe (1, 2) , Laetitia Jourdan (1, 2) , Thomas Legrand (2) , Jérémie Humeau (2) , El-Ghazali Talbi (1, 2)

1 LIFL - Laboratoire d'Informatique Fondamentale de Lille
2 DOLPHIN - Parallel Cooperative Multi-criteria Optimization

This chapter presents ParadisEO-MOEO, a white-box object-oriented software framework dedicated to the flexible design of metaheuristics for multi-objective optimization. This paradigm-free software proposes a unified view for major evolutionary multi-objective metaheuristics. It embeds some features and techniques for multi-objective resolution and aims to provide a set of classes allowing to ease and speed up the development of computationally efficient programs. It is based on a clear conceptual distinction between the solution methods and the problems they are intended to solve. This separation confers a maximum design and code reuse. This general-purpose framework provides a broad range of fitness assignment strategies, the most common diversity preservation mechanisms, some elitistrelated features as well as statistical tools. Furthermore, a number of state-of-the-art search methods, including NSGA-II, SPEA2 and IBEA, have been implemented in a user-friendly way, based on the fine-grained ParadisEO-MOEO components.

Domaines: Recherche opérationnelle [math.OC]

Arnaud Liefooghe, Laetitia Jourdan, Thomas Legrand, Jérémie Humeau, El-Ghazali Talbi. ParadisEO-MOEO: A Software Framework for Evolutionary Multi-Objective Optimization. Advances in Multi-Objective Nature Inspired Computing, Springer Berlin / Heidelberg, pp.87-117, 2010, ⟨10.1007/978-3-642-11218-8_5⟩. ⟨hal-00522623⟩