Abstract: The aim of this talk is to present a unified view of metaheuristic approaches for multi-objective optimization. Following three main issues dealing with fitness assignment, diversity preservation and elitism, a robust and flexible model is introduced. This model is validated by demonstrating how state-of-the-art methods can conveniently fit into it. Then, a modular implementation is proposed and is successfully integrated in a general purpose software framework dedicated to the reusable design of multi-objective metaheuristic optimization techniques such as evolutionary algorithms.<\/p>\n

Biography: El-Ghazali Talbi received the Master and Ph.D. degrees in Computer Science from the Institut National Polytechnique de Grenoble in France. He is a full Professor at the University of Lille and the head of DOLPHIN research group from both the Lille’s Computer Science laboratory (LIFL, Universit’e Lille 1, CNRS) and INRIA Lille Nord Europe. His current research interests are in the field of multi-objective optimization, parallel algorithms, metaheuristics, combinatorial optimization, cluster and cloud computing, hybrid and cooperative optimization, and applications to logistics\/transportation, bioinformatics and networks. Professor Talbi has to his credit more than 150 international publications including journal papers, book chapters and conferences proceedings.<\/p>\n