ParadisEO-MOEO: A Framework for Evolutionary Multi-objective Optimization

Abstract. This paper presents ParadisEO-MOEO, a white-box objectoriented generic framework dedicated to the flexible design of evolutionary multi-objective algorithms. This paradigm-free software embeds some features and techniques for Pareto-based 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 multi-objective problems they are intended to solve. This separation confers a maximum design and code reuse. ParadisEO-MOEO provides a broad range of archive-related features (such as elitism or performance metrics) and the most common Pareto-based fitness assignment strategies (MOGA, NSGA, SPEA, IBEA and more). Furthermore, parallel and distributed models as well as hybridization mechanisms can be applied to an algorithm designed within ParadisEO-MOEO using the whole version of ParadisEO. In addition, GUIMOO, a platform-indepen...

• Type: Conference
• Year: 2006
• Where: EMO
• Authors: Arnaud Liefooghe, Matthieu Basseur, Laetitia Jourdan, El-Ghazali Talbi
• Keywords: EMO 2006, Evolutionary Multi-objective Algorithms, Multi-objective Problems, Objectoriented Generic Framework, Optimization