桂林理工大学学报2017，Vol.37Issue(4)：699-706,8.DOI:10.3969/j.issn.1674-9057.2017.04.024
基于改进粒子群优化算法的Web服务组合
Web services composition based on modified particle swarm optimization
摘要
Abstract
It is an NP problem to generate the composition service fast and dynamically from a large number of candidate services under the users functional and non-functional requirements.Particle Swarm Optimization (PSO) is an effective approach to solve this kind of problem.There is some deficiency partly or entirely existing in services composition approaches based on PSO.It can only supporting specific workflow or the workflow includeding only sequence pattern.It can only use the number of iterations as the termination condition;not avoiding the premature convergence problem or the result of that being unsatisfactory.This paper proposes a web service composition method based on modified particle swarm optimization which supports sequence,parallel and choice patterns.The main improvements of our PSO are:adding a few initial particles generated by local optimization strategy;adjusting the setting proposal of cognitive factors and social factors;proposing the concept of diversity in the population and presenting a diversity of healing mechanisms to avoid premature convergence;setting an early termination condition of the iterative operations.The simulation experiments demonstrated the advantages of the proposal in time cost and method optimization.关键词
粒子群优化/Web服务组合/早熟收敛/提前终止条件Key words
particle swarm optimization/web services composition/premature convergence/early termination condition分类
信息技术与安全科学引用本文复制引用
陆湘鹏,叶恒舟..基于改进粒子群优化算法的Web服务组合[J].桂林理工大学学报,2017,37(4):699-706,8.基金项目
国家自然科学基金项目(51365010) （51365010）
广西自然科学基金项目(2014GXNSFBA118269) （2014GXNSFBA118269）
广西高校嵌入式技术与智能信息处理重点实验室开放基金项目(2016-01-02) （2016-01-02）
