An ensemble optimisation approach to service composition in cloud manufacturing

被引:32
|
作者
Fazeli, Mohammad Moein [1 ]
Farjami, Yaghoub [1 ]
Nickray, Mohsen [1 ]
机构
[1] Univ Qom, Dept Comp & IT, Qom, Iran
关键词
Cloud manufacturing (CMfg); service quality; service selection and scheduling; RESOURCE; ALGORITHM; SELECTION;
D O I
10.1080/0951192X.2018.1550679
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Cloud Manufacturing (CMfg) is a new popular and centralised management and service-oriented business model that enables on-demand access to a shared collection of diversified and distributed manufacturing resources. In CMfg, selecting the best combination of services to perform a customer's requests is the most important problem. To solve this problem, this paper proposes an ensemble optimisation approach (EOA) which combines other optimisation methods in a flexible and extensible way. To validate the performance of the EOA, several test cases are conducted. Computational results show that the EOA can find better solutions compared with other optimisation algorithms such as genetic algorithm, particle swarm optimisation and social spider optimisation.
引用
收藏
页码:83 / 91
页数:9
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