基于模拟退火遗传算法的服务选择

摘要

为了解决面向服务体系结构服务组合中服务选择问题,提出了一种将模拟退火算法与遗传算法相结合的融合算法.将服务流程等效成AOV图,对AOV图进行拓扑排序,并将生成的拓扑序列作为遗传算法的编码,使用QoS参数作为适应度,在遗传算法生成每一代子代后,利用模拟退火算法对其进行局部优化调整.仿真实验结果表明,模拟退火遗传算法在减少服务流程资源消耗上能取得理想的效果.%A combination of simulated annealing algorithm and genetic algorithm is proposed for solving the service selection during the service oriented architecture (SOA) services composition. First the service workflow is transferred into activity on vertex (AOV) graph equivalently, and then topological sort of the AOV graph is gotten. The topological sort is used as coding of the genetic algorithm, the quality of service (QoS) parameters is used as fitness of the genetic algorithm. After the generation of a new population by the genetic algorithm, an optimization is made by the simulated annealing algorithm. The result of the experimental simulation indicates that the simulated annealing genetic algorithm is effective.