Multi-Objective Memetic Algorithms

Multi-Objective Memetic Algorithms

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The series Studies in Computational Intelligence (SCI) publishes new developments and advances in the various areas of computational intelligence - quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems and hybrid intelligent systems. Critical to both contributors and readers are the short publication time and world-wide distribution - this permits a rapid and broad dissemination of research results.Tatsuya Okabe1, Yaochu Jin2, and Bernhard Sendhoff2 1 Honda Research Institute Japan Co., Ltd. (HRI-JP), 8-1 Honcho, Wako-Shi, ... Carl-Legien-Strasse 30, 63073 Offenbach/Main, Germany For tackling an multi-objective optimization problem (MOP), evolutionary computation (EC) ... The results show that the hybrid representation exhibits better and more stable performance than the original GA/ES.

Title:Multi-Objective Memetic Algorithms
Author:Chi-Keong Goh, Yew-Soon Ong, Kay Chen Tan
Publisher:Springer Science & Business Media - 2009-02-26


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