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An Optimal Allocation Method for Virtual Resource Considering Variable Metrics of Cloud Manufacturing Service

[+] Author Affiliations
Jin Cui, Lei Ren, Lin Zhang

Beihang University, Beijing, ChinaMinistry of Education, Beijing, China

Qiong Wu

Beihang University, Beijing, China

Paper No. MSEC2015-9245, pp. V002T04A013; 7 pages
  • ASME 2015 International Manufacturing Science and Engineering Conference
  • Volume 2: Materials; Biomanufacturing; Properties, Applications and Systems; Sustainable Manufacturing
  • Charlotte, North Carolina, USA, June 8–12, 2015
  • Conference Sponsors: Manufacturing Engineering Division
  • ISBN: 978-0-7918-5683-3
  • Copyright © 2015 by ASME


Based on the concept of Cloud Computing, a new service-oriented, high efficiency low consumption, knowledge-based, and intelligent networked agile manufacturing model Cloud Manufacturing (CMfg) has been proposed recently. The manufacturing resources optimization allocation model (MROAM) is one of the core parts for implementing CMfg. In this paper, a new MROAM is proposed in the background of CMfg system. In this model, variable metrics such as a variety of evaluation indicators for different types of manufacturing services are taken into account. In addition, time, cost, virtual manufacturing resource interface, and so on constrains are considered as well. To solve the manufacturing resources optimization allocation problem, a new improved intelligent algorithm named Kmeans-PSO was presented by combining the particle swarm optimization (PSO) algorithm and the K-means clustering. Experiment results demonstrate the effectiveness of the designed algorithm and show Kmeans-PSO’s high performances for addressing the manufacturing resources allocation problem compared with other intelligent algorithms.

Copyright © 2015 by ASME
Topics: Manufacturing



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