Solving weighted graph matching problem by modified microgenetic algorithm

Cheng Wen Liu, Kuo Chin Fan, Jorng Tzong Horng, Yuan Kai Wang

研究成果: 雜誌貢獻會議論文同行評審

4 引文 斯高帕斯(Scopus)

摘要

Microgenetic Algorithm(MGA) is Genetic Algorithm(GA) using a very small population size (population size < 20). The weighted graph matching problem (WGMP) receives tremendous attention in the field of pattern recognition recently. In this paper, a hybrid MGA with larger population is proposed to solved the weighted graph matching problem. In our hybrid microgenetic algorithm, many modules, such as local search algorithm, biased initial population, a modified selection scheme, and a refining procedure, are embedded to improve the performance of the algorithm. Experimental results show that our method outperforms a well-known method, the Symmetric Polynomial Transform (SPT), on most instances of the weighted graph matching problems.

原文???core.languages.en_GB???
頁(從 - 到)638-643
頁數6
期刊Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
1
出版狀態已出版 - 1995
事件Proceedings of the 1995 IEEE International Conference on Systems, Man and Cybernetics. Part 2 (of 5) - Vancouver, BC, Can
持續時間: 22 10月 199525 10月 1995

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