Study on the combination of genetic algorithms and ant Colony algorithms for solving fuzzy job shop scheduling problems
文献类型：会议论文
| 作者 | Song XY(宋晓宇); Zhu YL(朱云龙) ; Yin CW(尹朝万); Li FM(李富明)
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| 出版日期 | 2006 |
| 会议名称 | IMACS Multiconference on Computational Engineering in Systems Applications (CESA 2006) |
| 会议日期 | October 4-6, 2006 |
| 会议地点 | Beijing, China |
| 关键词 | genetic algorithms ant Colony algorithm Taboo Search algorithm fuzzy processing time |
| 页码 | 1904-1909 |
| 中文摘要 | by using a single algorithm to deal with fuzzy job shop scheduling problems, it is difficult to get a satisfied solution. In this paper we propose a combined strategy of algorithms to solve fuzzy job shop scheduling problems. This strategy adopts genetic algorithms and ant colony algorithms as a parallel asynchronous search algorithm. In addition, according to the characteristics of fuzzy Job Shop scheduling, we propose a concept of the critical operation, and design a new neighborhood search method based on the concept. Furthermore, an improved TS algorithm is designed, which can improve the local search ability of genetic algorithms and ant colony algorithms. The experimental results on 13 hard problems of benchmarks show that the average agreement index increases 6.37% than parallel genetic algorithms, and increases 9.45% than TSAB algorithm. Taboo search algorithm improves the local search ability of the genetic algorithm, and the combined strategy is effective. |
| 收录类别 | EI ; CPCI（ISTP） |
| 产权排序 | 1 |
| 会议主办者 | IMACS, IEEE SMC Soc, Tsinghua Univ, Ecole Centrale Lille, Ecole Natl Superieure Arts & Ind Textiles, Natl Nat Sci Fdn China |
| 会议录 | 2006 IMACS: Multiconference on Computational Engineering in Systems Applications, Vols 1 and 2
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| 会议录出版者 | TSINGHUA UNIVERSITY PRESS |
| 会议录出版地 | BEIJING |
| 语种 | 英语 |
| ISBN号 | 978-7-302-13922-5 |
| WOS记录号 | WOS:000244084601144 |
| 源URL | [http://ir.sia.cn/handle/173321/8282]  |
| 专题 | 沈阳自动化研究所_工业信息学研究室_先进制造技术研究室 |
| 推荐引用方式 GB/T 7714 | Song XY,Zhu YL,Yin CW,et al. Study on the combination of genetic algorithms and ant Colony algorithms for solving fuzzy job shop scheduling problems[C]. 见:IMACS Multiconference on Computational Engineering in Systems Applications (CESA 2006). Beijing, China. October 4-6, 2006. |
入库方式： OAI收割
来源：沈阳自动化研究所
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