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2006
Springer

Design Issues in a Multiobjective Cellular Genetic Algorithm

10 years 7 months ago
Design Issues in a Multiobjective Cellular Genetic Algorithm
In this paper we study a number of issues related to the design of a cellular genetic algorithm (cGA) for multiobjective optimization. We take as an starting point an algorithm following the canonical cGA model, i.e., each individual interacts with those ones belonging to its neighborhood, so that a new individual is obtained using the typical selection, crossover, and mutation operators within this neighborhood. An external archive is used to store the non-dominated solutions found during the evolution process. With this basic model in mind, there are many different design issues that can be faced. Among them, we focus here on the synchronous/asynchronous feature of the cGA, the feedback of the search experience contained in the archive into the algorithm, and two different replacement strategies. We evaluate the resulting algorithms using a benchmark of problems and compare the best of them against two state-of-the-art genetic algorithms for multiobjective optimization. The obtained ...
Antonio J. Nebro, Juan José Durillo, Franci
Added 22 Aug 2010
Updated 22 Aug 2010
Type Conference
Year 2006
Where EMO
Authors Antonio J. Nebro, Juan José Durillo, Francisco Luna, Bernabé Dorronsoro, Enrique Alba
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