全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

求解总拖期时间最小化流水车间调度问题的多智能体进化算法

DOI: 10.3724/SP.J.1004.2014.00548, PP. 548-555

Keywords: 流水车间调度,总拖期时间,多智能体,进化算法

Full-Text   Cite this paper   Add to My Lib

Abstract:

?针对总拖期时间最小化的置换流水车间调度问题(Totaltardinesspermutationflow-shopschedulingproblem)提出了一种基于多智能体的进化搜索算法.在该算法中,采用基于延迟时间排序的学习搜索策略(Tardinessrankbasedlearning),快速产生高质量的新个体,并根据概率更新模型进行智能体网格的更新进化.同时通过实验设计的方法探讨了算法参数设置对算法性能的影响.为了验证算法的性能,求解了Vallada标准测试集中540个测试问题,并将测试结果与一些代表算法进行比较,验证了该算法的有效性.

References

[1]  Liao J M, Huang C J. Tabu search for non-permutation flowshop scheduling problem with minimizing total tardiness. Applied Mathematics and Computation, 2010, 217(2): 557-567
[2]  Hasija S, Rajendran C. Scheduling in flowshops to minimize total tardiness of jobs. International Journal of Production Research, 2004, 42(11): 2289-2301
[3]  Armentano V A, Ronconi D P. Tabu search for total tardiness minimization in flowshop scheduling problems. Computers & Operations Research, 1999, 26(3): 219-235
[4]  Talip K, Bilal T, John W. Elite guided steady-state genetic algorithm for minimizing total tardiness in flowshops. Computers & Industrial Engineering, 2010, 58(2): 300-306
[5]  Li B B, Wang L, Liu B. An effective PSO-based hybrid algorithm for multi-objective permutation flow shop scheduling. IEEE Transactions on Systems, Man, and Cybernetics --Part A: Systems and Humans, 2008, 38(4): 818-831
[6]  Jiao Li-Cheng, Liu Jing, Zhong Wei-Cai, Coevolutionary Computation and Multiagent Systems. Beijng: Science Press, 2006. 205-224(焦李成, 刘静, 钟伟才. 协同进化计算与多智能体系统. 北京: 科学出版社, 2006. 205-224)
[7]  Sarker R A, Ray T. Agent-Based Evolutionary Search. Berlin: Springer-Verlag, 2010. 97-116
[8]  Zhong Wei-Cai, Liu Jing, Jiao Li-Cheng. Optimal approximation of linear systems by multi-agent genetic algorithm. Acta Automatica Sinica, 2004, 30(6): 933-938(钟伟才, 刘静, 焦李成. 多智能体遗传算法用于线性系统逼近. 自动化学报, 2004, 30(6): 933-938)
[9]  Stützle T. Applying iterated local search to the permutation flow shop problem, Technical Report, AIDA-98-04, FG Intellektik, FB Informatik, TU Darmstadt, 1998
[10]  Osman I, Potts C. Simulated annealing for permutation flow-shop scheduling. Omega, 1989, 17(6): 551-557
[11]  Montgomery D C. Design and Analysis of Experiments (5th Edition). Hoblken: John Wiley and Sons, 2000
[12]  Ruiz R, Maroto C, Alcaraz J. Two new robust genetic algorithms for the flowshop scheduling problem. Omega, 2006, 34(5): 461-476
[13]  Parthasarathy S, Rajendran C. A simulated annealing heuristic for scheduling to minimize mean weighted tardiness in a flowshop with sequence-dependent setup times of jobs --a case study. Production Planning and Control, 1997, 8(5): 475-483
[14]  Hasija S, Rajendran C. Scheduling in flowshops to minimize total tardiness of jobs. International Journal of Production Research, 2004, 42(11): 2289-2301
[15]  Vallada E, Rubén R. Genetic algorithms with path relinking for the minimum tardiness permutation flowshop problem. Omega, 2010, 38(1-2): 57-67
[16]  Ruiz R, Stützle T. A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem. European Journal of Operational Research, 2007, 177(3): 2033-2049
[17]  Zemel E. Measuring the quality of approximate solutions to zero-one programming problems. Mathematics of Operations Research, 1981, 6(3): 319-332
[18]  Kim Y D. Heuristics for flowshop scheduling problems minimizing mean tardiness. Journal of the Operational Research Society, 1993, 44(1): 19-28
[19]  Kim Y D, Lim H G, Park M W. Search heuristics for a flow shop scheduling problem in a printed circuit board assembly process. European Journal of Operational Research, 1996, 91(1): 124-143
[20]  Vallada E, Rubén R. Cooperative metaheuristics for the permutation flowshop scheduling problem. European Journal of Operational Research, 2009, 193(2): 365-376
[21]  Vallada E, Rubén R, Gerardo M. Minimising total tardiness in the m-machine flowshop problem: a review and evaluation of heuristics and metaheuristics. Computers & Operations Research, 2008, 35(4): 1350-1373

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133