# [1]孙学胜,曹玖新,刘波,等.基于多目标粒子群优化的服务选择算法[J].东南大学学报(自然科学版),2009,39(4):684-689.[doi:10.3969/j.issn.1001-0505.2009.04.007] 　Sun Xuesheng,Cao Jiuxin,Liu Bo,et al.Service selection algorithm based on multi-objective particle swarm optimization[J].Journal of Southeast University (Natural Science Edition),2009,39(4):684-689.[doi:10.3969/j.issn.1001-0505.2009.04.007] 点击复制 基于多目标粒子群优化的服务选择算法() 分享到： var jiathis_config = { data_track_clickback: true };

39

2009年第4期

684-689

2009-07-20

## 文章信息/Info

Title:
Service selection algorithm based on multi-objective particle swarm optimization

Author(s):
School of Computer Science and Engineering, Southeast University, Nanjing 210096, China

Keywords:

TP301.6;TP393.4
DOI:
10.3969/j.issn.1001-0505.2009.04.007

Abstract:
An efficient service selection algorithm based on a multi-objective particle swarm optimization algorithm, MOPSOSS, is proposed. First, the service selection problem is modeled as a multi-objective constrained combinatorial optimization problem. Then according to the domination concept, new component service set, whose size is far less than the original one, is constructed. The multi-objective particle swarm optimization is employed and then pareto optimal solutions are obtained. The theoretical analysis proves that MOPSOSS can correctly obtain global optimal solutions. Comparison with the genetic algorithm(GA)shows that under the problem size of greater than 150, the average running time of MOPSOSS is 7% of that of GA, that solution number and distribution scope is respectively 1.15 and 1.5 times higher than GA. Moreover, 75% of MOPSOSS solutions can dominate GA ones. As restriction strength increasing, MOPSOSS running time decreases and the solution quality does not evidently decrease. MOPSOSS can obtain adequate high quality solutions in a shorter time than GA.

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