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A multi-objective optimization algorithm based on subgroup stratified coarse-grained model and its application*
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DOI：10.1016/j.compeleceng.2021.107180.png)
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Low efficiency and the tendency to fall into local optimum are the major obstacles to web service composition optimization. In this paper, we propose a multi-objective optimization algorithm based on the subgroup stratified coarse-grained model to improve the performance of web service composition optimization. Compared to the general particle swarm optimization algorithms, the proposed algorithm improves population structure, dynamically adjusts evolution strategy and increases the local extremum's perturbation. We demonstrate a solution to the constrained multiobjective web service composition optimization problem based on the proposed algorithm. Theoretical analysis and experimental results show that it improves the performance of web service composition optimization.
Keyword:
Multi-objective optimization
Subgroup stratification
Coarse-grained model
Web service composition
期刊
C
IF:
4.9
论文数:
6.7K
被引数:
1.3W
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