自适应模糊粒子群算法求解IT服务优化选择问题  

An Effective AFPSO(Adaptive Fuzzy Particle Swarm Optimization) Algorithm for Obtaining Optimal Selection of IT Services

作　　者：王润孝[1] 杨云涛[1,2] 李俊亭[1,3] 

机构地区：[1]西北工业大学机电学院,陕西西安710072 [2]陕西省地方电力(集团)有限公司配电网研究中心,陕西西安710061 [3]西安石油大学经济管理学院,陕西西安710065

出　　处：《西北工业大学学报》2012年第6期911-918,共8页Journal of Northwestern Polytechnical University

基　　金：陕西省科学技术研究发展计划(2009K08-21)资助

摘　　要：为了解决IT服务选择问题,提出了一种基于自适应模糊粒子群算法的IT服务优化选择方法。首先,针对业务流程对IT服务的需求,建立了以响应时间、执行费用、可靠性、可用度为目标的IT服务优化选择模型。然后,设计了求解模型的粒子群优化算法,应用模糊推理规则,自适应调整粒子进化过程中的自身学习因子和全局学习因子,以提高粒子收敛速度和全局搜索能力,从而获取了满足业务流程QoS约束的较优IT服务单元。最后以算例验证了模型及算法的可行性和有效性。Sections 1 and 2 of the full paper explain our AFPSO algorithm mantioned in the title, which we believe is effective. The core of sections 1 and 2 consists of： （ 1 ） according to the requirements of business processes in IT services, an optimal selection model of IT services was established; response time, execution cost, reliability and availability were set as its objective functions; （2） an optimization algorithm to solve the model was designed; the self learning factor and global learning factor were adaptively tuned by the fuzzy inference rules so as to improve the convergence speed and global searching ability; （3） the optimal IT service unit which satisfied the QoS constrai- ning condition of business process was obtained. Section 3 gives an application example; test results, presented in Table 5, and their analysis confirm preliminarily indeed the effectiveness of the proposed model and our AFPSO al- gorithm.

关 键 词：IT服务选择 粒子群优化 学习因子 服务质量 隶属函数 

分 类 号：TP391.7[自动化与计算机技术—计算机应用技术]