一种基于维度识别的协同进化算法

A Coevolutionary Algorithm Based on Dimension Identifying

为了探索如何在协同进化算法中结合问题域固有的结构信息,实施全局稳定进展,本文首先分析问题维度所体现的个体间收益特征,提出一种维度识别方法.在此基础上,设计并实现一个协同进化算法.它能在进化过程中通过个体间的交互收益自动鉴别问题维度,并保存每个维度上当前已搜索到的最高测试值,以此作为评价基准控制进化在所有维度上均单调进展.配套设计的结构文档不仅有效支持维度鉴别,准确提供当前全局最高进展信息,而且存档量能达到最小化来保证算法的有效实施.模拟实验证实了该算法的可行性,并显示该算法较其它同类算法具有更高的性能和效率.

How to integrate the dimensional information of the problem domain into coevolution is studied. Through the analysis of the outcome characteristics of interactions between individuals, a strict dimension identifying method is proposed. Thus, an efficient and reliable coevolutionary algorithm is designed. It can automatically identify dimensions of the problem by the outcome characteristics between individuals with only the current highest test in each dimension maintained and monotonic progress on all dimensions sustained. In this algorithm, the archive can achieve minimum size to guarantee its practicability. Experimental comparisons demonstrate that the algorithm performs more efficiently than others.