An effective service trust evaluation and preprocessing approach considering multi-user interests in cloud manufacturing
Weiqing Xiong, Ming K. Lim, Ming‐Lang Tseng, Chao Wang
Abstract
In the cloud manufacturing (CMfg) platform, there are numerous manufacturing services with same or similar functions. Due to the inconsistency of service quality, how to effectively evaluate the quality of services is a fundamental problem in CMfg, and which aims to reduce risk and increase the benefits of users. Under these contexts, this study first constructs a comprehensive three-dimensional trust evaluation system that considers the trust of service demanders, resource providers, and cloud platform operators in CMfg. And then, a manufacturing services trust evaluation and preprocessing model is proposed, and the optimization process is described as following: (1) superior and inferior manufacturing services are identified by the first stage filtration; and (2) inferior manufacturing services are further classified by the second stage filtration. After that, to deal with the concerned problem, an improved multi-objective non-dominated sorting genetic algorithm III (IMO-NSGA-III) is developed to find the Pareto-optimal solutions. Furthermore, nine random instances are designed to show that the proposed IMO-NSGA-III outperforms other three state-of-the-art algorithms in terms of convergence and diversity. Finally, three case studies that comes from an automotive parts assembly company is employed, and the effectiveness of the proposed model and IMO-NSGA-III algorithm is further demonstrated.