| Mixed Self-adapting GA Optimal Scheduling Algorithm for a Multiple Resource Job-shop |
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| 作者姓名： | LI Shu-juan LI Yan LIU Zhi-gang |
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| 作者单位： | School of Mechanical and Instrumental Engineering, Xi＇an Universityof Technology, Xi＇an 710048, P. R. China |
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| 摘 要： | With an aim at the job-shop scheduling problem of multiple resource constraints, this paper presents mixed self-adapting Genetic Algorithm （ GA ） , and establishes a job-shop optimal scheduling model of multiple resource constraints based on the effect of priority scheduling rules in the heuristic algorithm upon the scheduling target. New coding regulations or rules are designed. The sinusoidal function is adopted as the self-adapting factor, thus making cross probability and variable probability automatically change with group adaptability in such a way as to overcome the shortcoming in the heuristic algorithm and common GA, so that the operation efficiency is improved. The results from real example simulation and comparison with other algorithms indicate that the mixed self-adapting GA algorithm can well solve the job-shop optimal scheduling problem under the constraints of various kinds of production resources such as machine-tools and cutting tools.
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| 关 键 词： | 启发式规则 混合自调节遗传算法 多资源约束 最优规划 |
| 修稿时间： | 2007-10-11 |
Mixed Self-adapting GA Optimal Scheduling Algorithm for a Multiple Resource Job-shop |
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| LI Shu-juan,LI Yan,LIU Zhi-gang.Mixed Self-adapting GA Optimal Scheduling Algorithm for a Multiple Resource Job-shop[J].International Journal of Plant Engineering and Management,2007,12(3):160-170. |
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| Authors: | LI Shu-juan LI Yan LIU Zhi-gang |
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| Abstract: | With an aim at the job-shop scheduling problem of multiple resource constraints, this paper presents mixed self-adapting Genetic Algorithm (GA), and establishes a job-shop optimal scheduling model of multiple resource constraints based on the effect of priority scheduling rules in the heuristic algorithm upon the scheduling target. New coding regulations or rules are designed. The sinusoidal function is adopted as the self-adapting factor, thus making cross probability and variable probability automatically change with group adaptability in such a way as to overcome the shortcoming in the heuristic algorithm and common GA, so that the operation efficiency is improved. The results from real example simulation and comparison with other algorithms indicate that the mixed self-adapting GA algorithm can well solve the job-shop optimal scheduling problem under the constraints of various kinds of production resources such as machine-tools and cutting tools. |
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| Keywords: | heuristic rule mixed self-adapting GA multiple resource constraint optimal scheduling |
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