LZW Mutual-Information-Maximizing Input Clustering Algorithm

摘要：

This paper proposes a new evolutionary algorithm called LZWMIMIC. The proposed algorithm combines the LZW compressed chromosome encoding and MutualInformation-Maximizing Input Clustering (MIMIC) algorithm. The advantage of LZW encoding is that it reduces the search space thus speeds up the evolutionary search. The advantage of MIMIC is that it can solve complex problem by finding a relationship between gene positions. The performance of the original MIMIC and LZWMIMIC are compared on standard benchmark problems. Further, compressed chromosome length and problem size are varied to see their effect in the performance. The experimental results show that our proposed algorithm outperforms the original MIMIC.

关键词： LZW MIMIC EDA

作者: Orawan Watchanupaporn Worasait Suwannik

作者单位: Department of Computer Science Kasetsart University Bangkok, Thailand

会议类型: 国际会议

会议名称: 2011 Seventh International Conference on Natural Computation(第七届自然计算国际会议 ICNC 2011)

会议地点: 上海

会议语种:英文

页码: 1123-1126

在线出版日期: 2011-07-26（万方平台首次上网日期，不代表论文的发表时间）