基于云模型蚁群优化的制造服务调度策略  

Manufacturing service scheduling strategy based on cloud model ant colony optimization

作　　者：张卫[1] 潘晓弘[1] 刘志[2] 董天阳[2] 张玲[1,3] 

机构地区：[1]浙江大学现代制造工程研究所,浙江杭州310027 [2]浙江工业大学计算机学院,浙江杭州310032 [3]浙江科技学院经济管理学院,浙江杭州310012

出　　处：《计算机集成制造系统》2012年第1期201-207,共7页Computer Integrated Manufacturing Systems

基　　金：浙江省科技计划重大资助项目(2008C01060);国家863计划资助项目(2007AA04Z101);国家科技支撑计划资助项目(2006BAF01A22)~~

摘　　要：为快速响应制造企业用户在线使用制造服务,建立了制造服务调度模型,采用制造服务调度器产生服务的分配方案,通过接口进行制造服务选择,完成对用户服务申请的响应。提出基于服务质量的制造服务选择模型,该模型利用服务质量参数的约束,保证了制造服务申请的响应质量。结合云模型和蚁群算法对制造服务调度问题制定求解策略,利用云模型有效限制了蚁群算法陷入局部最优解。通过30个服务申请10个接口调度的算例分析,表明了该策略的可行性,且云模型蚁群优化取得了较模拟退火算法更好的优化结果。To respond online manufacturing service use quickly by manufacturing enterprise users,the scheduling model for manufacturing service was established,and the allocation scheme was generated by manufacturing service dispatcher.The user service application response was completed by selecting manufacturing service through interface.Manufacturing service selection model based on service quality was proposed.Through using service parameter constraints,the application response quality of manufacturing service was guaranteed.The solution strategy was formulated by integrating the union cloud model and the Ant Colony Optimization（ACO）,and ACO was limited to falling into the partial optimal solution effectively by using union cloud model.The example analysis for 30 services application in 10 interfaces scheduling demonstrated that the strategy was feasible,and the cloud model ACO obtained better optimization result comparing to the simulated annealing algorithm.

关 键 词：制造服务 云模型 蚁群算法 服务选择 服务分配 调度 

分 类 号：TH166[机械工程—机械制造及自动化]