摘要
基于对云物流环境下服务组合问题特点的分析,构建了多路径云物流服务组合过程模型。结合云物流服务组合路径多样性、结构复杂性及资源按时刻表触发等特点,采用多属性效用函数理论,研究建立了基于最大效用度的带触发时刻表的多路径服务组合数学模型。针对模型求解过程中存在的可变长度任务链选择、触发时刻表处理、全局QoS计算等环节,提出融合串行调度的混合遗传算法对模型进行求解。结合具体物流任务运作实例,对模型和算法的有效性及可行性进行了验证。
Based on the analysis of service composition＇s features in cloud logistics environment, a multi-path cloud logistics services composition process model was built. Through considering the characteristics of path diversity, structure complexity and resources trigger with timetable of cloud logistics service composition, a maximum utility multi-path service composition mathematical model with trigger timetable was established by using multi-attribute u- tility function theory. In view of variable task chain length, triggering timetable and global QoS calculation in the process of solving the model, a hybrid genetic algorithm by fusion of serial scheduling was proposed. Combined with a logistics instance, the feasibility and effectiveness of proposed model and algorithm were verified.
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2015年第6期1617-1625,共9页
Computer Integrated Manufacturing Systems
基金
国家科技支撑计划资助项目(2015BAH46F01)
重庆市科技攻关计划资助项目(CSTC
2012ggC0001
2012gg-yyjs00010
2014yykfA40006)
江西省教育厅科技计划资助项目(GJJ14536)
中央高校基本科研业务费跨学科类重大资助项目(CDJZR12118801)
高等学校博士学科点专项科研基金资助项目(20130191110045)
重庆大学汽车协同创新中心专项资助项目(CDJZR12110080)~~
关键词
多路径
触发时刻表
物流云服务组合
混合遗传算法
多属性效用理论
multi-path
trigger timetable
cloud logistics service composition
hybrid genetic algorithm
multi-attribute utility theory
