| 274 | 9 | 351 |
| 下载次数 | 被引频次 | 阅读次数 |
柔性作业车间的合理调度是提高生产效率和效益的关键,为了解决柔性作业车间调度问题求解过程中的难题,提出一种改进人工免疫算法的柔性作业车间调度方法.首先对当前柔性作业车间调度的研究现状进行分析,然后基于总加工时间最短构建数学模型,采用人工免疫算法进行求解,并针对标准人工免疫算法存在的不足,引入粒子群算法保持种群的多样性,以避免出现局部最优解,最后采用标准算例集对算法的性能进行仿真测试.结果表明,相对于其他算法,改进人工免疫算法获得了较优的柔性作业车间调度方案,尤其在解决大规模问题时,优势更加显著.
Abstract：A novel flexible job shop scheduling method based on improved artificial immune algorithm was proposed. Mathematical model of the flexible job shop scheduling was established,and the total shortest processing time was taken as the objective function. The particle swarm optimization algorithm as the operator was embedded into artificial immune algorithm to maintain the diversity of population and prevent obtaining local optimal solution. The performance of the algorithm was tested by simulation experiments on standard set. Results showed that compared with other algorithms,the proposed algorithm could obtain better flexible job shop scheduling scheme,especially large-scale problems.
[1]曾强,沈玲,潘启东,等.批量生产柔性作业车间多目标精细化调度方法[J].计算机工程与应用,2014,50(2):263-270.
[2]GUO Y D,LUN S X.Flow shop scheduling problem with partial skill flexibility of workers[J].Journal of Bohai university,2013,34(2):232-236.
[3]FENG M Y.A grouping particle swarm optimization algorithm for flexible job shop scheduling problem[C]∥Proceedings of IEEE Pacific-asia Workshop on Computational Intelligence and Industrial Application.Wuhan,2008:332-336.
[4]RUIZ R,VAZQUEZ R J A.The hybrid flow shop scheduling problem[J].European journal of operational research,2010,205(1):1-18.
[5]KAHRAMAN C,ENGIN O,KAYA I,et al.Multiprocessor task scheduling in multistage hybrid flow-shops:a parallel greedy algorithm approach[J].Applied soft computing,2010,10(4):1293-1300.
[6]ZHANG G H,ZHANG L J,WANG Y C,et al.An effective hybrid particle swarm optimization algorithm for flexible job-shop scheduling problem[J].The open automation and control systems journal,2014,6(1):1604-1611.
[7]王长明,聂建军.基于遗传算法的二次曲面提取技术研究[J].郑州大学学报(理学版),2013,45(1):65-68.
[8]刘长平,叶春明.置换流水车间调度问题的萤火虫算法求解[J].工业工程与管理,2012,17(3):56-59.
[9]宋雪枫,融合蚁群算法和遗传算法的矩形件排样问题研究[D].郑州:郑州大学,2011.
[10]唐建平,宋红生,王东署.一种移动机器人动态环境下的路径规划[J].郑州大学学报(理学版),2012,44(1):75-78.
[11]薛宏全,魏生民,张鹏,等.基于多种群蚁群算法的柔性作业车间调度研究[J].计算机工程与应用,2013,49(24):243-248.
[12]申丽君,刘丽,陆锐,等.基于改进免疫进化算法的云计算任务调度[J].计算机工程,2012,38(9):208-210.
[13]宋存利.求解柔性作业调度问题的协同进化粒子群算法[J].计算机工程与应用,2013,49(21):15-18.
[14]ALVAREZ V R,FUERTES A,TAMARIT J M,et al.A heuristic to schedule flexible job shop in a glass factory[J].European journal of operational research,2005,165(2):525-534.
基本信息:
DOI：10.13705/j.issn.1671-6841.2015288
中图分类号:TP18;TB497
引用信息:
[1]张永强,高锐敏.改进人工免疫算法求解柔性作业车间调度问题[J],2016,48(02):53-57.DOI:10.13705/j.issn.1671-6841.2015288.
基金信息:
国家自然科学基金资助项目(61202285);; 南省科技攻关项目(132102210501)
2015-12-05
2015
2016-04-26
2016
2