双资源多目标集成协作计划与调度模型及其求解算法
A Multi-Objective Integrated Model and Its Algorithm of Collaborative Planning and Scheduling for Dual-Resource
DOI: 10.12677/MSE.2017.62009, PDF, HTML, XML, 下载: 1,459  浏览: 4,797  科研立项经费支持
作者: 胡倩倩, 马陈程, 孙越, 包振强, 阚云：扬州大学信息工程学院，江苏 扬州
关键词: 协作计划；多目标；集成模型；双资源调度；Collaborative Planning； Multi-Objective； Integrated Model； Dual-Resource Scheduling
摘要: 针对现有生产系统中协作计划、生产计划以及调度方案不能同步制定的问题，考虑在供应链环境下有协作的计划与调度，建立了以完工时间最短、加工成本最低以及总拖期最短为目标的包含机器设备和操作工人两种约束资源的双资源多目标集成协作计划与调度模型。设计了SPEA2算法，在其中设计了既适合双资源要求又能满足协作决策要求的包含工序编码、机器编码、工人编码以及协作决策变量的染色体对编码方式，并对染色体的交叉变异等操作进行了改进。最后，用仿真实验来验证本文模型的正确性及算法的有效性。
Abstract: Since the problem of that collaborative plan, manufacturing plan and the scheduling solutions are hard to be paralleled and synchronized, the multi-objective model of integrated collaborative plan and scheduling for dual-resource is established, taking the collaborative planning into considera-tion under the environment of supply chain. There are three objectives in the model: the shortest completion time, the lowest cost and the minimum total tardiness. Take machines and workers as two kinds of constrained resources. Then, the improved SPEA2 algorithm is designed. In this algo-rithm, the chromosome pair encoding which is suitable for dual-resource and collaborative decision is designed. It includes the process coding, the machine coding, the worker coding and the collabo-rative decision variable. Finally, the correctness of the model and the efficiency of the algorithm are proved by the simulation experiment.
文章引用：胡倩倩, 马陈程, 孙越, 包振强, 阚云. 双资源多目标集成协作计划与调度模型及其求解算法[J]. 管理科学与工程, 2017, 6(2): 71-82. https://doi.org/10.12677/MSE.2017.62009

参考文献

[1] 何旭红, 黄祥瑞. 工业系统中人的可靠性分析: 原理、方法与应用[M]. 北京: 清华大学出版社, 2007.
[2] Betul, Y. and Mutlu, Y.M. (2010) A Multi-Objective Ant Colony System Algorithm for Flow Shop Scheduling Problem. Expert Systems with Applications, 37, 1361-1368.
https://doi.org/10.1016/j.eswa.2009.06.105
[3] Mahdi, N. and Nasim, N. (2013) An Interactive Algorithm for Multi-Objective Flow Shop Scheduling with Fuzzy Processing Time through Resolution Method and TOPSIS. International Journal of Advanced Manufacturing Technology, 66, 1047-1064.
https://doi.org/10.1007/s00170-012-4388-5
[4] Voratas, K. and Siriwan, S. (2011) A Two-Stage Genetic Algorithm for Multi-Objective Job Shop Scheduling Problems. Journal of Intelligent Manufacturing, 22, 355-365.
https://doi.org/10.1007/s10845-009-0294-6
[5] 李兢尧, 孙树栋, 黄媛, 牛刚刚. 求解双资源约束车间调度问题的继承式双目标遗传算法[J]. 控制与决策, 2011, 26(12): 1761-1767.
[6] Xu, J., Xu, X. and Xie, S.Q. (2011) Recent Devel-opments in Dual Resource Constrained (DRC) System Research. European Journal of Operational Research, 215, 309-318.
https://doi.org/10.1016/j.ejor.2011.03.004
[7] 方叶祥, 钱存华, 蒋南云, 郑宝龙, 崔志勇. 基于遗传禁忌算法的双资源约束下并行生产线调度研究[J]. 运筹与管理, 2007, 16(5): 153-158.
[8] 鞠全勇, 朱剑英. 双资源多工艺路线作业车间模糊调度问题研究[J]. 机械科学与技术, 2006, 25(12): 1424-1427.
[9] Zamiska, J.R., Jaber, M.Y. and Kher, H.V. (2007) Worker Deployment in Dual Resource Constrained Systems with a Task-Type Factor. European Journal of Operational Research, 177, 1507-1519.
https://doi.org/10.1016/j.ejor.2005.04.018
[10] 刘晓霞, 蔡刚毅, 谢里阳. 双资源作业车间双目标调度优化研究[J]. 组合机床与自动化加工技术, 2009(10): 107-112.
[11] Kher, H.V. (2000) Examination of Flexibility Acquisition Policies in Dual Resource Constrained Job Shops with Simultaneous Worker Learning and Forgetting Effects. Journal of the Operational Research Society, 51, 592-601.
https://doi.org/10.1057/palgrave.jors.2600935
[12] Salum, L. and Araz, O.U. (2009) Using the When/Where Rules in Dual Re-source Constrained Systems for a Hybrid Push-Pull Control. International Journal of Production Research, 47, 1661-1677.
https://doi.org/10.1080/00207540701579530
[13] Bokhorst, J.A.C., Slomp, J. and Gaalman, G.J.C. (2004) On the Who-Rule in Dual Resource Constrained (DRC) Manufacturing Systems. International Journal of Production Research, 42, 5049-5074.
https://doi.org/10.1080/00207540410001733878
[14] Bernd, S.R., Jens, H. and Torsten, H. (2010) Analysis of Priority Rule-Based Scheduling in Dual-Resource-Con- strained Shop-Floor Scenarios. International Conference on Advances in Machine Learning and Systems Engineering, Springer Verlag, Berkeley, 269-281.
[15] Elmaraghy, H., Patel, V. and Abdallah, I.B. (2000) Scheduling of Manufacturing Systems under Dual-Resource Constraints Using Genetic Algorithms. Journal of Manufacturing Systems, 19, 186-198.
https://doi.org/10.1016/S0278-6125(00)80011-4
[16] Li, J.Y., Sun, S.D., Huang, Y. and Wang, N. (2011) Solving Dual Re-source Constrained Job-Shop Scheduling Problem (DRCJSP) Based on Hybrid Ant Colony Algorithm with Self-Adaptive Parameters. Journal of Northwestern Polytechnical University, 29, 54-61.
[17] 袁亮, 袁逸萍, 袁志玲, 孙文磊. 双资源柔性车间多目标调度优化研究[J]. 组合机床与自动化加工技术, 2013(12): 149-152.
[18] EI Marghy, H. (1999) A Genetic Algorithm Based Approach for Scheduling of DRC-Resource Constrained Manufacturing Systems. Annals of the CIRP, 369-372.
[19] 孙志峻. 双资源车间智能优化调度[J]. 东南大学学报, 2005, 35(3): 376-381.
[20] Kumar, M. and Rajotia, S. (2003) Integration of Scheduling with Computer Aided Process Planning. Journal of Materials Processing Technology, 138, 297-300.
https://doi.org/10.1016/S0924-0136(03)00088-8
[21] Chryssolouris, G., Chan, S. and Cobb, W. (1984) Decision Making on the Factory Floor: An Integrated Approach to Process Planning and Scheduling. Robotics and Computer-Integrated Manufacturing, 1, 9-315.
https://doi.org/10.1016/0736-5845(84)90020-6
[22] Bao, Z.Q., Ding, Q.X., Zhu, J.W., Wang, C. and Wang, F.F. (2012) Mul-ti-Objective Integrated Manufacturing Collaborative Planning and Scheduling Based on Pareto Optimal. Computer Integrated Manu-facturing Systems, 18, 2419- 2426.
[23] Jbid, A. (2013) An Integrated Fuzzy Approach for Information Technology Planning in Col-laborative Product Development. 7th IFAC Conference on Manufacturing Modelling Management and Control, 1985-1990.
[24] Zhou, H., Wang, J. and Tan, X.W. (2007) Hybrid Collaborative Evolutionary Algorithm for Integrated Production Planning. Computer Inte-grated Manufacturing Systems, 13, 1412-1418.
[25] 吴秀丽, 孙树栋, 杨展, 翟颖妮. 多目标柔性Job Shop调度问题的技术现状和发展趋势[J]. 计算机应用研究, 2007, 24(3): 1-9.
[26] Chryssolouris, G., Chan, S. and Cobb, W. (1984) Decision Making on the factory Floor: An Integrated Approach to Process Planning and Scheduling. Robotics and Computer-Integrated Manufacturing, 1, 9-315.
https://doi.org/10.1016/0736-5845(84)90020-6
[27] Bao, Z.Q., Ding, Q.X., Zhu, J.W., Wang, C. and Wang, F.F. (2012) Mul-ti-Objective Integrated Manufacturing Collaborative Planning and Scheduling Based on Pareto Optimal. Computer Integrated Manu-facturing Systems, 18, 2419- 2426.
[28] Jbid, A. (2013) An Integrated Fuzzy Approach for Information Technology Planning in Col-laborative Product Development. 7th IFAC Conference on Manufacturing Modelling Management and Control, 1985-1990.
[29] Zhou, H., Wang, J. and Tan, X.W. (2007) Hybrid Collaborative Evolutionary Algorithm for Integrated Production Planning. Computer Inte-grated Manufacturing Systems, 13, 1412-1418.
[30] Beckendorff, U., Kreutzfeldt, J. and Ullmann, W. (1991) Reactive Workshop Scheduling Based on Alternative Routings. Proceedings of a Conference on Factory Automation and Information Management, Boca Roton, CRC Press, 75- 85.
[31] Kumar, P.R., Ajai, J. and Rajiv, V. (2013) An Approach for Integration of Process Planning and Scheduling. International Journal of Computer Integrated Manufacturing, 26, 284-302.
https://doi.org/10.1080/0951192X.2012.684721
[32] 郑金华. 多目标进化算法及其应用[M]. 北京: 科学出版社, 2007: 51-60.

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