Volume 30, Issue 4 (IJIEPR 2019)                   IJIEPR 2019, 30(4): 405-427 | Back to browse issues page

DOI: 10.22068/ijiepr.30.4.405


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1- Department of Industrial Engineering, Yazd University, Yazd, Iran.
2- Department of Industrial Engineering, Yazd University, Yazd, Iran. , mhonarvar@yazd.ac.ir
3- School of Mechanical Engineering, Shandong University, Jinan 250061, China
Abstract:   (287 Views)
There is still a great deal of attention in cellular manufacturing systems and proposing capable metaheuristics to better solve these complicated optimization models. In this study, machines are considered unreliable that life span of them follows a Weibull distribution. The intra and inter-cell movements for both parts and machines are determined using batch sizes for transferring parts are related to the distance traveled through a rectilinear distance. The objectives minimize the total cost of parts relocations and maximize the processing routes reliability due to alternative process routing. To solve the proposed problem, Genetic Algorithm (GA) and two recent nature-inspired algorithms including Keshtel Algorithm (KA) and Red Deer Algorithm (RDA) are employed. In addition, the main innovation of this paper is to propose a novel hybrid metaheuristic algorithm based on the benefits of aforementioned algorithms. Some numerical instances are defined and solved by the proposed algorithms and also validated by the outputs of exact solver. A real case study is also utilized to validate the proposed solution and modeling algorithms. The results indicate that the proposed hybrid algorithm is more appropriate than the exact solver and outperforms the performance of individual ones.
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Type of Study: Research | Subject: Manufacturing Process & Systems
Received: 2019/06/11 | Accepted: 2019/09/15 | Published: 2019/12/3