4.7 Article

A cooperative approach to service booking and scheduling in cloud manufacturing

期刊

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
卷 273, 期 3, 页码 861-873

出版社

ELSEVIER
DOI: 10.1016/j.ejor.2018.09.007

关键词

Scheduling; Cloud manufacturing; Client coordination; Service booking; Manufacturing synchronization

资金

  1. National Natural Science Foundation of China [51705250, 51675442]
  2. Natural Science Foundation of Jiangsu Province [BK20170797]
  3. Fundamental Research Funds for the Central Universities [NR2017014]
  4. Zhejiang Provincial government
  5. Hangzhou Municipal government
  6. Lin'an City government

向作者/读者索取更多资源

Cloud manufacturing (CMfg) can make mass manufacturing resources more widely accessible to clients in the form of manufacturing services with their available time slots and the associated prices. In decentralized cases, clients can select optimal services to fulfill their individual demand. This paper proposes that clients can coordinate with each other for the exchange and reutilization of their booked resources. Via client coordination cost savings are derived from the post-optimization of the initial uncoordinated solution of all clients at the planning horizon. The optimization problem, which is a service booking and scheduling problem, has been proved to be strong NP-hard. Besides, we consider manufacturing synchronization (MfgSync) when scheduling a client's job on multiple resources, which includes simultaneity of completing the sub-tasks of a client's manufacturing job and punctuality of fulfilling the job. Optimal solution algorithms based on dynamic programming are proposed for two common cases. Considering the selfishness of each client, the success of the coordination depends on whether every participant can be better off than to act independently. We develop a cooperative game for client coordination and propose a core cost savings allocation scheme with which every client can get benefits through coordination. Based on the allocation scheme, clients tend to form a grand coalition. The computational results show that our approach can make substantial cost savings for clients. (C) 2018 Elsevier B.V. All rights reserved.

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