Title: Selection of resource service chain with conflict-free dependencies in cloud manufacturing systems

Authors: Haibo Li; Juncheng Tong; Zheng Zhang; Yongbo Yu; Xiuyang Lei

Addresses: College of Computer Science and Technology, Huaqiao University, Xiamen Engineering Research Center of Enterprise Interoperability and Business Intelligence, Xiamen 361021, China ' College of Computer Science and Technology, Huaqiao University, Xiamen 361021, China ' College of Computer Science and Technology, Huaqiao University, Xiamen 361021, China ' College of Computer Science and Technology, Huaqiao University, Xiamen 361021, China ' College of Computer Science and Technology, Huaqiao University, Xiamen 361021, China

Abstract: In cloud manufacturing (CMfg), to improve the efficiency of a whole business process, all distributed manufacturing resources services should be selected as 'service flows', called resource-service chain (RSC). However, selecting an RSC with conflict-free dependency is more difficult in collaborative manufacturing than in a centralised one, as resource services are usually selected independently by different organisations. To overcome this shortcoming, an algorithm based evolutionary algorithm is proposed. First, five common types of dependencies are defined after analysing the relationship among manufacturing resources. Then, genetic algorithm (GA) is applied to find the optimal set of RSCs, in which the dependencies among resource services are considered as constraint rules. Finally, a collaborative business process is taken as an instance to verify the selection of RSCs with conflict-free dependency. The results show that it can improve the efficiency of resource service selection.

Keywords: cloud manufacturing; CMfg; resource-service chain; RSC; conflict; dependency; genetic algorithm; evolutionary algorithm.

DOI: 10.1504/IJIMS.2020.107945

International Journal of Internet Manufacturing and Services, 2020 Vol.7 No.3, pp.216 - 236

Received: 20 Feb 2018
Accepted: 05 Nov 2018

Published online: 05 Apr 2020 *

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