基于多规则资源分配的柔性作业车间调度问题多目标集成优化方法

摘要/Abstract

摘要：

摘要：针对柔性作业车间调度问题中多种资源分配的复杂特性，建立了以最小完工时间、最优人工分配方案、设备最大负荷以及最小生产成本为目标的集成优化模型，并设计了一种具有多重资源约束的多目标集成优化方法；针对组合模型的爆炸性特征，为降低模型的复杂度，采用多规则资源分配的集成调度思想，通过调整规则概率使概率大的规则被优先选中，使用多规则导向机制“推动”搜索过程向指定目标方向移动, 并结合动态规划法求解最优人员分配方案；采用改进的非支配排序遗传算法——NSGAⅡ可以获得不同规则概率值的Pareto解集;最后，通过仿真对比与应用验证了所提方法的有效性.

关键词: , 柔性作业车间调度, 多目标集成优化, 多规则, 多重资源, 改进的非支配排序遗传算法

Abstract:

Abstract： In order to reduce the complexity of multi-objective optimization in flexible jobshop scheduling and improve optimization efficiency, a multiobjective integrated optimization method with multiple resource constraints was proposed in this paper. Firstly, an integrated optimization model was established according to the objectives of minimum completion time, optimal human resource allocation plan, maximum equipment load and lowest production costs. Besides, in view of the explosive characteristics of combination model, an integrated scheduling rule for multiple resources allocation was presented to reduce the model complexity. As for the selection strategies of the scheduling rules, the rules with a high probability were preferentially selected through adjusting the probability of rules. In addition, the multiplerule guiding mechanism was adopted to push the search process toward the target direction. Furthermore, the improved nondominated sorting genetic algorithm (NSGAⅡ) was adopted to obtain the Pareto solution sets of different probability values of the rules. Finally, the effectiveness of the proposed method was verified by simulation comparison.

Key words: , flexible job-shop scheduling； multi-objective integrated optimization； multirule； multiple resources； non-dominated sorting genetic algorithm

中图分类号:

TP 39

高丽1a,2,周炳海2,杨学良1b,王吉霞1a. 基于多规则资源分配的柔性作业车间调度问题多目标集成优化方法[J]. 上海交通大学学报（自然版）, 2015, 49(08): 1191-1198.

GAO Li1a,2,ZHOU Binghai2,YANG Xueliang1b,Wang Jixia1a. A MultiObjective Integrated Optimization Method for FJSP Based on Multi-Rule Resource Allocation[J]. Journal of Shanghai Jiaotong University, 2015, 49(08): 1191-1198.

参考文献

［1］Browning T R, Yassine A A. Resourceconstrained multiproject scheduling: Priority rule performance revisited［J］. International Journal Production Economics，2010，126(2)：212228.

［2］Chen James C, Wu ChengChun, Chen ChiaWen, et al. Flexible job shop scheduling with parallel machines using Genetic Algorithm and Grouping Genetic Algorithm ［J］. Expert Systems with Applications，2012，39(11)：1001610021.

［3］Yuan Yuan, Xu Hua. Flexible job shop scheduling using hybrid differential evolution algorithms ［J］. Computers & Industrial Engineering，2013，65(2)：246260.

［4］Chen Binchao, Timothy I Matis. A flexible dispatching rule for minimizing tardiness in job shop scheduling ［J］. International Journal Production Economics，2013，141(1)：361365.

［5］Seren Ozmehmet Tasana, Mitsuo Gen. An integrated selection and scheduling for disjunctive network problems ［J］. Computers & Industrial Engineering，2013，65(1)：6576.

［6］Liao Shuhsien, Hsieh Chialin, Lai Pengjen. An evolutionary approach for multiobjective optimization of the integrated location–inventory distribution network problem in vendormanaged inventory ［J］. Expert Systems with Applications，2011，38(6)：67686776.

［7］Moradi E, Fatemi Ghomi S M T，Zandieh M. Biobjective optimization research on integrated fixed time interval preventive maintenance and production for scheduling flexible jobshop problem ［J］. Expert Systems with Applications, 2011，38(6)：71697178.

［8］Yang Jianbo, Xu Dongling, Yang Shanlin. Integrated efficiency and tradeoff analyses using a DEAoriented interactive minimax reference point approach ［J］. Computers & Operations Research， 2012，39(5)：10621073.

［9］Tyson R Browning, Ali A Yassine． Resourceconstrained multiproject scheduling: Priority rule performance revisited ［J］. International Journal Production Economics， 2010，126(2)：212228.

［10］Jolai F, Asefi H, Rabiee M，et al. Biobjective simulated annealing approaches for nowait twostage flexible flow shop scheduling problem ［J］．Scientia Iranica, Transactions E: Industrial Engineering， 2013，20(3)：8611 872.

［11］He Yaohua, Hui Chiwai. A rulebased genetic algorithm for the scheduling of singlestage multiproduct batch plants with parallel units ［J］. Computers and Chemical Engineering， 2008，32(12)：30673083.

［12］Hamid Reza Qodmanan，Mahdi Nasiri，Behrouz MinaeiBidgoli. Multi objective association rule mining with genetic algorithm without specifying minimum support and minimum confidence ［J］. Expert Systems with Applications, 2011，38(1)：288298.

［13］Philippe FournierViger, Usef Faghihi, Roger Nkambou, et al. CMRules: Mining sequential rules common to several sequences ［J］. KnowledgeBased Systems，2012，25(1)：6376.

［14］Wang Shijin, Liu Ming. A heuristic method for twostage hybrid flow shop with dedicated machines ［J］. Computers & Operations Research，2013，40(1)：438450.

［15］Yang Xibei, Xie Jun, Song Xiaoning, et al. Credible rules in incomplete decision system based on descriptors ［J］. KnowledgeBased Systems，2009，22(1)：817.

［16］吴秀丽，孙树栋，余建军，等. 多目标柔性作业车间调度优化研究［J］. 计算机集成制造系统，2006, 12 (5)：731736.

WU Xiuli，SUN Shudong，YU Jianjun，et al. Research on multiobjective optimization for flexible job shop scheduling［J］. Computer Integrated Manufacturing Systems，2006，12 (5)：731736.

［17］Lu Hui, Niu Ruiyao, Liu Jing, et al. A chaotic nondominated sorting genetic algorithm for the multiobjective automatic test task scheduling problem［J］. Applied Soft Computing， 2013，22(5)：27902812.

［18］Hsie Machine, Chang Chingjung, Yang ITung, et al. Resourceconstrained scheduling for continuous repetitive projects with timebased production units ［J］. Automation in Construction，2009，18(7)：942946.

［19］Ghasem Moslehi，Mehdi Mahnam. A Pareto approach to multiobjective flexible jobshop scheduling problem using particle swarm optimization and local search ［J］. International Journal Production Economics，2011，129(1)：1422.

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