Multi-task scheduling game with limited resources for cloud manufacturing
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TP391.7

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    Abstract:

    To solve the cloud service composition optimal-selection (CSCOS) problem in cloud manufacturing (CMfg), based on the deep analysis of the difficulties and shortcomings in current researches, an optimization model for multi-task scheduling with limited resources problem (MLSR) is proposed. Considering the interest conflicts of service demanders and important quality of service (QoS) indicators, the multi-task scheduling problem with limited resources is converted into multiple static non-cooperative game, and the service demander (SD), different execution manufacturing path of each task and comprehensive service level (CSL) are considered as game player, game strategy and game payoff of a game, respectively. On this basis, the process to seek the pure strategy Nash Equilibrium (PSNE) solution is compiled into an algorithm, whose solutions are the final manufacturing execution paths for each task. Finally, simulation results show the feasibility, effectiveness of both the model and algorithm.

    Reference
    [1] 李伯虎, 张霖, 王时龙, 等. 云制造:面向服务的网络化制造新模式[J]. 计算机集成制造系统, 2010, 16(1):1-7,16.LI Bohu, ZHANG Lin, WANG Shilong, et al. Cloud manufacturing:a new service-oriented networked manufacturing model[J]. Computer Integrated Manufacturing Systems, 2010, 16(1):1-7,16.(in Chinese)
    [2] 李伯虎, 张霖, 任磊, 等. 再论云制造[J]. 计算机集成制造系统, 2011, 17(3):449-457.LI Bohu, ZHANG Lin, REN Lei, et al. Further discussion on cloud manufacturing[J]. Computer Integrated Manufacturing Systems, 2011, 17(3):449-457. (in Chinese)
    [3] 李正龙. 一种n人静态博弈纯策略纳什均衡存在性判别法[J]. 运筹与管理, 2004, 13(1):33-37.LI Zhenglong. An existence distinguishing method for pure strategy Nash equilibrium existence in n-person static games[J]. Operations Research and Management Science, 2004, 13(1):33-37.(in Chinese)
    [4] Zhou J J, Yao X F. Multi-objective hybrid artificial bee colony algorithm enhanced with Lévy flight and self-adaption for cloud manufacturing service composition[J]. Applied Intelligence, 2017, 47(3):721-742.
    [5] 苏凯凯, 徐文胜, 李建勇, 等. 云制造环境下基于双层规划的资源优化配置方法[J]. 计算机集成制造系统, 2015, 21(7):1941-1952.SU Kaikai, XU Wensheng, LI Jianyong, et al. Manufacturing resource allocation method based on bi-level programming in cloud manufacturing[J]. Computer Integrated Manufacturing Systems, 2015, 21(7):1941-1952.(in Chinese)
    [6] Cao Y, Wang S L, Kang L, et al. A TQCS-based service selection and scheduling strategy in cloud manufacturing[J]. International Journal of Advanced Manufacturing Technology, 2016, 82(1-4):235-251.
    [7] Zhou J, Yao X. Hybrid teaching-learning-based optimization of correlation-aware service composition in cloud manufacturing[J]. International Journal of Advanced Manufacturing Technology, 2017:1-19.
    [8] Huang B Q, Li C H, Tao F. A chaos control optimal algorithm for QoS-based service composition selection in cloud manufacturing system[J]. Enterprise Information Systems, 2014, 8(4):445-463.
    [9] Xue X, Wang S F, Lu B Y. Manufacturing service composition method based on networked collaboration mode[J]. Journal of Network and Computer Applications, 2016, 59:28-38.
    [10] 刘卫宁,刘波,孙棣华.面向多任务的制造云服务组合[J].计算机集成制造系统, 2013, 19(1):199-209.LIU Weining, LIU Bo, SUN Dihua, et al. Multi-task oriented service composition in cloud manufacturing[J]. Computer Integrated Manufacturing Systems, 2013, 19(1):199-209. (in Chinese)
    [11] 苏凯凯, 徐文胜, 李建勇. 云制造环境下基于非合作博弈的资源优化配置方法[J]. 计算机集成制造系统, 2015, 21(8):2228-2239.SU Kaikai, XU Wensheng, LI Jianyong. Manufacturing resource allocation method based on non-cooperative game in cloud manufacturing[J]. Computer Integrated Manufacturing Systems, 2015, 21(8):2228-2239.(in Chinese)
    [12] Liu Y K, Xu X, Zhang L, et al. Workload-based multi-task scheduling in cloud manufacturing[J]. Robotics and Computer-Integrated Manufacturing, 2017, 45:3-20.
    [13] 马文龙, 王铮, 赵燕伟, 等. 基于改进蚁群算法的制造云服务组合优化[J]. 计算机集成制造系统, 2016, 22(1):113-121.MA Wenlong, WANG Zheng, ZHAO Yanwei, et al. Optimizing services composition in cloud manufacturing based on improved ant colony algorithm[J]. Computer Integrated Manufacturing Systems, 2016, 22(1):113-121.(in Chinese)
    [14] Rasmusen E. Games and information:an introduction to games theory[J]. The Economic Journal, 1989, 99(397):864.
    [15] Nawa N E. Agents that acquire negotiation strategies using a game theoretic learning theory[J]. International Journal of Intelligent Systems, 2006, 21(1):5-39.
    [16] Marco G D, Romaniello M. Beliefs correspondences and equilibria in ambiguous games[J]. International Journal of Intelligent Systems, 2012, 27(2):86-107.
    [17] 张超勇, 董星, 王晓娟, 等. 基于改进非支配排序遗传算法的多目标柔性作业车间调度[J]. 机械工程学报, 2010, 46(11):156-164.ZHANG Chaoyong, DONG Xing, WANG Xiaojuan, et al. Improved NSGA-Ⅱ for the multi-objective flexible job-shop scheduling problem[J]. Journal of Mechanical Engineering, 2010, 46(11):156-164.(in Chinese)
    [18] He W, Sun D H. Scheduling flexible job shop problem subject to machine breakdown with route changing and right-shift strategies[J]. International Journal of Advanced Manufacturing Technology, 2013, 66(1-4):501-514.
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舒萧,王时龙,康玲,杨波,杨星星,邹海旭.面向云制造的有限资源多任务调度博弈[J].重庆大学学报,2020,43(3):1~11

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  • Received:March 31,2019
  • Online: March 31,2020
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