Title :
A unified model for evolutionary multi-objective optimization and its implementation in a general purpose software framework
Author :
Liefooghe, Arnaud ; Jourdan, Laetitia ; Talbi, El-Ghazali
Author_Institution :
LIFL, Univ. des Sci. et Technol. de Lille, Villeneuve d´´Ascq
fDate :
March 30 2009-April 2 2009
Abstract :
The aim of this paper is to propose a unified view of evolutionary approaches for multi-objective optimization. Following three main issues dealing with fitness assignment, diversity preservation and elitism, a robust and flexible model, based on a fine-grained decomposition, 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 evolutionary multi-objective optimization techniques.
Keywords :
evolutionary computation; software reusability; diversity preservation; elitism; evolutionary multiobjective optimization; fine-grained decomposition; fitness assignment; general purpose software framework; Decision making; Design optimization; Europe; Evolutionary computation; Open source software; Optimization methods; Robustness; Software reusability;
Conference_Titel :
Computational intelligence in miulti-criteria decision-making, 2009. mcdm '09. ieee symposium on
Conference_Location :
Nashville, TN
Print_ISBN :
978-1-4244-2764-2
DOI :
10.1109/MCDM.2009.4938833