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Published in:
2009 | OriginalPaper | Chapter
Study on Improving the Fitness Value of Multi-objective Evolutionary Algorithms
Authors : Yong Gang Wu, Wei Gu
Published in: Cutting-Edge Research Topics on Multiple Criteria Decision Making
Publisher: Springer Berlin Heidelberg
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Pareto sort classification method is often used to compute the fitness value of evolutionary groups in multi-objective evolutionary algorithms. However this kind of computation may produce great selection pressure and result in premature convergence. To address this problem, an improved method to compute the fitness value of multi-objective evolutionary algorithms based on the relative relationship between objective function values is proposed in this paper, which improves the convergence and distribution of multi-objective evolutionary algorithms. Testing results of test functions show that the improved computation method has a higher ability of convergence and distribution than the evolutionary algorithm based on Pareto sort classification method.