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面向云制造的有限资源多任务调度博弈
引用本文: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(自然科学版),2020,43(3):1-11.
作者姓名:舒萧  王时龙  康玲  杨波  杨星星  邹海旭
作者单位:重庆大学 机械传动国家重点实验室, 重庆 400044,重庆大学 机械传动国家重点实验室, 重庆 400044,重庆大学 机械传动国家重点实验室, 重庆 400044,重庆大学 机械传动国家重点实验室, 重庆 400044,重庆大学 机械传动国家重点实验室, 重庆 400044,重庆大学 机械传动国家重点实验室, 重庆 400044
基金项目:国家科技支撑计划资助项目(2015BAF02B02);教育部创新团队发展计划资助项目(IRT_15R64)。
摘    要:为解决云制造环境下云服务组合优化调度问题,在深入分析目前优化调度问题存在的难点及研究不足的基础上,提出一种云制造环境下有限资源的多任务调度模型。考虑服务需求者间存在的利益冲突及重要的服务评价指标,以每个服务需求者作为博弈参与者,将每个任务的执行制造路径当作博弈策略,把时间、合格率、成本和服务质量组成的综合服务水平看作博弈支付函数,最终把有限资源的多任务调度问题转变为多个静态非合作博弈问题。在此基础上,将求解纯策略纳什均衡解的过程编制为算法,该算法所得的均衡解为每个任务的最终执行制造路径。实验仿真表明该模型及算法具有可行性及有效性。

关 键 词:云制造  多任务调度  有限资源  非合作博弈  纳什均衡
收稿时间:2019/3/31 0:00:00

Multi-task scheduling game with limited resources for cloud manufacturing
SHU Xiao,WANG Shilong,KANG Ling,YANG Bo,YANG Xingxing and ZOU Haixu.Multi-task scheduling game with limited resources for cloud manufacturing[J].Journal of Chongqing University(Natural Science Edition),2020,43(3):1-11.
Authors:SHU Xiao  WANG Shilong  KANG Ling  YANG Bo  YANG Xingxing and ZOU Haixu
Institution:State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, P. R. China,State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, P. R. China,State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, P. R. China,State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, P. R. China,State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, P. R. China and State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, P. R. China
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.
Keywords:cloud manufacturing  multi-task scheduling  limited resources  non-cooperative game  Nash Equilibrium
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