Organizational evolutionary applied on geometric constraints solving

Duo Wang, Wenhui Li, Rongqing Yi, X. Cheng
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Abstract

In this paper, a new optimization method, Organizational Evolutionary Algorithm (OEA), is proposed, in which a population is made of organizations and whose evolution is led by three organizational evolutionary operators, i.e. the splitting operator, the merging operator and the cooperating operator; the splitting operator controls the size of organizations and make part of organizations enter into next generation directly, which are benefit for keeping the diversity of populations; the merging operator acts as a local searching function with taking advantage of leaders information; the cooperating operator increases the adaptability degree through the interactions of organizations. OEA is successfully applied to solve the non-linear parameterization design problems. Experiments show that OEA performs better than original Generic algorithm (GA) in this application of parameterization design.
组织演化在几何约束求解中的应用
本文提出了一种新的优化方法——组织进化算法(organization evolution Algorithm, OEA),该算法将组织组成一个群体,其进化由三个组织进化算子(即分裂算子、合并算子和合作算子)领导;分裂算子控制组织的规模,使部分组织直接进入下一代,有利于保持种群的多样性;合并算子作为局部搜索函数,利用领导者信息;合作操作者通过组织间的相互作用提高了组织的适应性。将OEA成功地应用于非线性参数化设计问题。实验表明,在参数化设计的应用中,OEA算法的性能优于原有的通用算法(GA)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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