An ensemble optimisation approach to service composition in cloud manufacturing. Issue 1 (2nd January 2019)

• Record Type: Journal Article
• Authors: Fazeli, Mohammad Moein; Farjami, Yaghoub; Nickray, Mohsen
• Is Part Of: International journal of computer integrated manufacturing. Volume 32:Issue 1(2019)
• Page Start: 83
• Page End: 91
• Publication Date: 2019-01-02
• Subjects: Cloud manufacturing (CMfg) -- service quality -- service selection and scheduling; Computer integrated manufacturing systems -- Periodicals; 670.427
• DOI: 10.1080/0951192X.2018.1550679
• Languages: English
• ISSNs: 0951-192X

Abstract

ABSTRACT: 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.