| Summary: | 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.
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