面向Pareto最优遗传算法的服务组合方法  

Pareto Optimality Based Genetic Algorithm in Web Services Composition

作　　者：胡焕耀[1,2] 董渭清[1] 符锐[1] 张星[1] 赵晓昳[1] 

机构地区：[1]西安交通大学电子与信息工程学院,西安710049 [2]中兴通讯股份有限公司上海研发中心,上海201203

出　　处：《西安交通大学学报》2009年第12期50-54,共5页Journal of Xi'an Jiaotong University

基　　金：国家自然科学基金资助项目(60773118);国家高技术研究发展计划资助项目(2006AA01A109)

摘　　要：为了解决Pareto遗传算法在每一次进化操作中都要构造当前进化群体最优解集而影响运行效率的问题,提出了一种面向Pareto最优遗传算法的服务组合方法,以实现Web服务组合的全局优化.用伪二叉树法则构造目标函数的Pareto最优集合,再进行Pareto最优解集排序,最后采用个体相似度计算来确定遗传算法的适应度函数,由此获得一组满足约束条件的Pareto最优解服务集合.实验验证表明,所提方法可以提高多目标遗传算法处理服务组合效率的问题,即使在服务规模较大的情况下,所获得的解与最优值的比率仍能接近90%的水平.A new method of service selection is proposed to implement the global optimal selection of Web services, and to avoid the routine in a genetic algorithm where an optimal evolving set is built for every current evolving operation to impose a negative influence on the efficiency of the algorithm. The pseudo binary tree＇s rule is used to produce a set of optimal Pareto solutions. Then the optimal Pareto solutions are sequenced and individuals ＇ similarity of each Pareto solution is calculated to determine the fitness function in the genetic algorithm. Experimental results show of proposed method generates a result that has a similarity up to 90% compared with the optimal result, even in the case of a large number of services.

关 键 词：WEB服务组合 全局优化 遗传算法 PARETO最优 

分 类 号：TP305[自动化与计算机技术—计算机系统结构]