自适应遗传算法求解模糊作业车间调度问题

杨建斌; 孙树栋; 牛刚刚; 王萌

自适应遗传算法求解模糊作业车间调度问题

1.
西北工业大学系统集成与工程管理研究所, 西安 710072

基金项目:

国家自然科学基金项目(51075337,50705076)资助

详细信息

作者简介:
杨建斌(1986-),硕士研究生,研究方向为计算机集成制造和车间调度智能算法,howwhat@126.com;孙树栋,教授,博士生导师,sdsun@nwpu.edu.cn

杨建斌(1986-),硕士研究生,研究方向为计算机集成制造和车间调度智能算法,howwhat@126.com;孙树栋,教授,博士生导师,sdsun@nwpu.edu.cn

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出版历程
- 收稿日期: 2011-11-01

Adaptive Genetic Algorithm for Fuzzy Job-shop Scheduling Problem

1.
Institute of System Integration and Engineering Management, Northwestern Polytechnical University, Xi'an 710072

摘要

摘要: 研究模糊作业车间调度问题(FJSSP),用三角模糊数表示模糊加工时间,用半梯形模糊数表示模糊交货期,以最大化最小客户满意度为调度目标,建立了模糊环境下Job-shop调度问题的模型。提出了一种自适应遗传算法,该算法采用基于优先列表的编码方式,提高了编码效率;在进化过程中对种群采用精英保留策略,确保最优个体不被破坏;并对自适应交叉变异算子进行了改进,使种群最优个体参与进化。仿真结果证明所提算法在寻优能力及收敛性能方面均有所改善。
- 模糊作业车间调度 /
- 自适应遗传算法 /
- 精英保留
Abstract: The fuzzy job-shop scheduling problem is studied in this paper. Fuzzy processing times were denoted bytriangular fuzzy numbers and fuzzy due dates were presented by half trapezoid fuzzy numbers. Based on the agree-ment index to maximize the minimum customer satisfaction,the model of fuzzy job-shop scheduling problem wasproposed. Furthermore,a new adaptive genetic algorithm was proposed,which promoted the coding efficiency byutilizing the coding method based on preferred list. Also,elitism preservation was adopted in the evolution processand adaptive crossover-mutation operator was improved so that the optimum individual can participate in the evolu-tion. At last,the improvement of the new algorithm in both search ability and convergence performance were veri-fied by the simulation results.
- fuzzy job-shop scheduling problem /
- adaptive genetic algorithm /
- elitism strategy

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参考文献(13)

[1]	Gen M,et al. Solving job-shop scheduling problems with fuzzyprocessing time using genetic algorithms[A]. Proceedings of2th European Conference on Intelligent Techniques and SoftComputing[C],1994
[2]	谢源,谢剑英,邓小龙. 混合优先约束下带模糊交货期的单机调度问题的研究[J]. 信息与控制,2005,34(3):369～372
[3]	Lin Feng-Tse. A job-shop scheduling problem with fuzzy process-ing times[A]. Lecture Notes in Computer Science[C],2001,2074:409～418
[4]	Sakawa M,Mori T. An efficient genetic algorithm for job-shop sched-uling problems with fuzzy processing time and fuzzy duedate[J].Computers and Industrial Engineering,1999,36:325～341
[5]	杨宏兵,严洪森,陈琳. 知识化制造环境下模糊调度模型和算法[J]. 计算机集成制造系统,2009,15(7):1374～1382
[6]	顾擎明,曹丽娟,宋文忠. 解 Job-shop 调度问题的自适应遗传算法[J]. 控制与决策,1998,13(5):589～593
[7]	沈斌,周莹君,王家海. 基于自适应遗传算法的 Job-shop 调度问题研究[J]. 计算机应用,2009,29:161～164
[8]	顾幸生. 不确定性条件下的生产调度[J]. 华东理工大学学报,2000,26(5):441～446
[9]	Bingul Z. Adaptive genetic algorithms applied to dynamic mul-tiobjective problems[J]. Applied Soft Computing,2007,7:791～799
[10]	Sakawa M,Kubota R. Fuzzy programming for multiobjective Job-shop scheduling with fuzzy processing time and fuzzy duedatethrough genetic algorithm[J]. European Journal of Opera-tional Research,2000,120(2):393～407
[11]	牛刚刚,孙树栋,余建军,马彦. 免疫进化算法求解静态 Job-shop 调度[J]. 机械工程学报,2006,42(5):87～91
[12]	Deb K,Agrawal S. Understanding interactions among geneticalgorithm parameters[A]. Foundations of Genetic Algorithms5[C],San Francisco: Morgan Kauffman,1998:265～286
[13]	Srinivas M,Patnaik L M. Adaptive probabilities of crossover andmutation in genetic algorithms[J]. IEEE Transactions on Sys-tems,Man and Cybernetics,1994,24(4):17～26