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Main Authors: Yue, Hao, Wu, Yingtao, Wang, Min, Hu, Hesuan, Wu, Weimin, Zhang, Jihui
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2406.19608
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author Yue, Hao
Wu, Yingtao
Wang, Min
Hu, Hesuan
Wu, Weimin
Zhang, Jihui
author_facet Yue, Hao
Wu, Yingtao
Wang, Min
Hu, Hesuan
Wu, Weimin
Zhang, Jihui
contents Cloud manufacturing system is a service-oriented and knowledge-based one, which can provide solutions for the large-scale customized production. The service resource allocation is the primary factor that restricts the production time and cost in the cloud manufacturing customized production (CMCP). In order to improve the efficiency and reduce the cost in CMCP, we propose a new framework which considers the collaboration among services with the same functionality. A mathematical evaluation formulation for the service composition and service usage scheme is constructed with the following critical indexes: completion time, cost, and number of selected services. Subsequently, a problem decomposition based genetic algorithm is designed to obtain the optimal service compositions with service usage schemes. A smart clothing customization case is illustrated so as to show the effectiveness and efficiency of the method proposed in this paper. Finally, the results of simulation experiments and comparisons show that these solutions obtained by our method are with the minimum time, a lower cost, and the fewer selected services.
format Preprint
id arxiv_https___arxiv_org_abs_2406_19608
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Multi-service collaboration and composition of cloud manufacturing customized production based on problem decomposition
Yue, Hao
Wu, Yingtao
Wang, Min
Hu, Hesuan
Wu, Weimin
Zhang, Jihui
Systems and Control
J.0
Cloud manufacturing system is a service-oriented and knowledge-based one, which can provide solutions for the large-scale customized production. The service resource allocation is the primary factor that restricts the production time and cost in the cloud manufacturing customized production (CMCP). In order to improve the efficiency and reduce the cost in CMCP, we propose a new framework which considers the collaboration among services with the same functionality. A mathematical evaluation formulation for the service composition and service usage scheme is constructed with the following critical indexes: completion time, cost, and number of selected services. Subsequently, a problem decomposition based genetic algorithm is designed to obtain the optimal service compositions with service usage schemes. A smart clothing customization case is illustrated so as to show the effectiveness and efficiency of the method proposed in this paper. Finally, the results of simulation experiments and comparisons show that these solutions obtained by our method are with the minimum time, a lower cost, and the fewer selected services.
title Multi-service collaboration and composition of cloud manufacturing customized production based on problem decomposition
topic Systems and Control
J.0
url https://arxiv.org/abs/2406.19608