遗传算法中的目标函数分解

Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600) Pub Date : 2002-05-12 DOI:10.1109/CEC.2002.1006260

K. G. Khoo, P. N. Suganthan

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引用次数: 0

摘要

遗传算法自提出以来，已被应用于许多优化问题。在这里，解字符串的每个元素的信息被提取，以提高遗传算法的性能。我们解耦一个适应度评估函数，估计每个维度的适应度贡献。利用这些信息，每个溶液中的每个维度都在为自己在后代中的位置而战。与标准遗传算法的比较表明，该遗传算法在常用测试函数上优于标准遗传算法。

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Objective function decomposition within genetic algorithm

The genetic algorithm (GA) has been applied to numerous optimization problems since its introduction. Here, information on each element of the solution strings is extracted to improve the GA's performance. We decouple a fitness evaluation function, estimating the fitness contribution by each dimension. Using this information, each dimension within each solution fights for its position in the offspring. A comparison with the standard GA showed that the proposed GA is superior on commonly tested functions.

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Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)

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