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 Mutual-Information-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.