文章基本信息

标题：Innately Split Model for Job-shop Scheduling Problem
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作者：Kokolo Ikeda ; Sigenobu Kobayashi
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2002
卷号：17
期号：5
页码：530-538
DOI：10.1527/tjsai.17.530
出版社：The Japanese Society for Artificial Intelligence
摘要：Job-shop Scheduling Problem (JSP) is one of the most difficult benchmark problems. GA approaches often fail searching the global optimum because of the deception UV-structure of JSPs. In this paper, we introduce a novel framework model of GA, Innately Split Model (ISM) which prevents UV-phenomenon, and discuss on its power particularly. Next we analyze the structure of JSPs with the help of the UV-structure hypothesys, and finally we show ISM's excellent performance on JSP.
关键词：job-shop scheduling problem ; genetic algorithm ; deception ; uv-phenomenon ; innately split model