摘要： 对于大量功能相似而服务质量不同的Web服务，服务组合优化可使其满足客户不同需求并被广泛应用，但现有Web服务组合优化方法普遍存在搜索效率低和寻优不精准的问题。为此，提出一种改进的花朵授粉算法，通过实现全局搜索和局部搜索的动态转换，促进种群优化。将差分进化算法的变异和交换操作加入到花朵授粉算法中，增强花朵的有效性和多样性，同时利用贪心策略选择适应度值高的花朵，加快算法收敛速度，增强其寻优能力。实验结果表明，与DE、KDE、FPA和EFPA算法相比，该算法在求解服务组合问题上具有更快的收敛速度和更好的寻优性能。

关键词: 花朵授粉算法, 差分进化, Web服务组合, 服务质量, 全局优化

Abstract: For a large number of Web services with similar functions and different qualities,Web service composition optimization can enable them to meet different needs of customers and be widely used.To address the low search efficiency and inaccurate optimization of existing service composition optimization methods,this paper proposes an Improved Flower Pollination Algorithm(IFPA),which realizes the dynamic transformation between global search and local search to promote population optimization.The mutation and exchange of the differential evolutionary algorithm are added to FPA to enhance the efficiency and diversity of flowers.Also,the greedy strategy is used to select flowers with high fitness value to accelerate the convergence and enhance the optimization ability of the algorithm.The experimental results show that,compared with DE algorithm,KDE algorithm,FPA algorithm and EFPA algorithm,the proposed algorithm has faster convergence speed and better optimization performance in solving service composition problem.

Key words: Flower Pollination Algorithm(FPA), Differential Evolution(DE), Web service composition, Quality of Service(QoS), global optimization

中图分类号: 

• TP18