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首页> 外文期刊>Electrical engineering in Japan >Proposal of a cannibalism bug-based search strategy using genetic algorithms (C-BUGS) and its application to multiobjective optimization problems
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Proposal of a cannibalism bug-based search strategy using genetic algorithms (C-BUGS) and its application to multiobjective optimization problems

机译：基于食人错误的基于遗传算法（C-BUGS）的搜索策略的建议及其在多目标优化问题中的应用

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摘要

For decision support under a multiobjective environment, it is effective to offer a Pareto optimal solution set with uniform distribution to the decision-maker. In this paper, a new optimization method for obtaining a Pareto optimal solution set with such uniform distribution is proposed. In order to overcome the difficulty of realizing this goal, the concept of cannibalism is introduced in BUGS (a bug-based search strategy using genetic algorithms). Introducing the concept of cannibalism achieves the uniform distribution of Pareto optimal solutions. A numerical experiment using typical continuous and discrete multiobjective optimization problems clarifies the usefulness of the proposed method.
机译：对于多目标环境下的决策支持，有效的是向决策者提供均匀分布的Pareto最优解决方案集。提出了一种获得具有均匀分布的帕累托最优解集的新方法。为了克服实现此目标的困难，在BUGS（使用遗传算法的基于错误的搜索策略）中引入了同类相食的概念。引入食人主义的概念可以实现帕累托最优解的均匀分布。使用典型的连续和离散多目标优化问题进行的数值实验阐明了该方法的实用性。

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