A new manufacturing service selection and composition method using improved Flower Pollination Algorithm
With the increase in the number of manufacturing services,how to select and compose these manufacturing services has become an increasingly challenging issue.It can be regarded as a multi-objective optimization problem that involves a variety of quality of service (QoS) attributes that are in conflict with each other.In this study,a multi-objective optimization model of manufacturing service composition is presented that is based on QoS and an environmental index.Next,the skyline operator is applied to reduce the solution space.And then a new method is proposed for solving the problem of manufacturing service selection and composition,which not only extends the basic Flower Pollination Algorithm (FPA) but also combines it with Differential Evolution (DE) algorithm to improve the performance of basic FPA.Finally,a case study is conducted to compare the proposed method with other evolutionary algorithms such as the Genetic Algorithm,DE,basic FPA,and extended FPA.The experimental results indicate that the proposed method performs best in terms of solving the problem of manufacturing service selection and composition.
Manufacturing service Service selection Service composition Skyline operator Improved Flower Pollination Algorithm
Zhang,W.Y. Yang,Y.S. Zhang,S. Xu,Y.B.
Zhejiang University of Finance and Economics, Hangzhou, Zhejiang 310018
国内会议
杭州
英文
165-183
2016-11-01（万方平台首次上网日期，不代表论文的发表时间）