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一种多层次制造服务建模和组合优选方法
丁涛1, 闫光荣1, 雷毅1,2, 徐翔宇1     
1. 北京航空航天大学 机械工程及自动化学院, 北京 100083;
2. 智能化协同制造技术及应用国家工程实验室, 北京 100094
摘要: 为提高云制造环境下服务建模和组合优选的准确性,首先将制造服务分多个层次进行描述,从资源服务、功能服务和流程服务3个层次进行建模。然后针对多层次服务模型,采用服务执行时间、服务花费成本和服务用户评价等因素构建服务组合优选的质量评估函数。为解决多层次服务的组合优选问题,提出一种改进引力搜索算法(NGSA),将小生境中的拥挤度因子和适应值共享技术引入传统引力搜索算法(GSA)以提高收敛速度和准确性。算例验证表明,相比传统的遗传算法(GA)和粒子群优化(PSO)算法,NGSA能在较短的时间内收敛,且最优解的匹配准确度更高。
关键词: 云制造     多层次建模     组合优选     小生境     引力搜索算法(GSA)    
A method of multi-level manufacturing service modeling and combinatorial optimal-selection
DING Tao1, YAN Guangrong1, LEI Yi1,2, XU Xiangyu1     
1. School of Mechanical Engineering and Automation, Beihang University, Beijing 100083, China;
2. National Engineering Laboratory for Intelligent Collaborative Manufacturing Technology and Application, Beijing 100094, China
Received: 2018-11-05; Accepted: 2019-02-22; Published online: 2019-03-18 11:07
Foundation item: National Science and Technology Major Project (2018ZX04001006)
Corresponding author. YAN Guangrong, E-mail: yangr@buaa.edu.cn
Abstract: In order to improve the accuracy of service modeling and combinatorial optimal-selection in cloud manufacturing, a multi-level modeling methodology is proposed to describe manufacturing services, which subdivided the service into three fine-grained levels:resource service, function service and process service. From the perspective of QoS indexes, the relationship among execution, time service cost and user evaluation for different service levels are analyzed and elaborated, and the corresponding evaluation objective functions of services composition are established. A niching behavior based gravitational search algorithm (NGSA) is designed to address manufacturing services composition problem, in which the niche crowding factor and fitness sharing technology are applied to gravitational search algorithm (GSA) to improve its convergence speed and accuracy. Finally, the simulation research results demonstrate that the NGSA algorithm can search better solution with less time-consumption than the traditional algorithms such as genetic algorithm (GA) and particle swarm optimization (PSO) algorithm.
Keywords: cloud manufacturing     multi-level modeling     combinatorial optimal-selection     niche     gravitational search algorithm (GSA)    

随着用户个性化需求的增加和网络化技术的发展,制造业面临交货周期缩短和制造能力不足的挑战。云制造[1]的提出将云服务技术扩展到生产制造领域,作为一种新的面向服务的网络化制造模式,云制造提供了一个无缝连接的、稳定