Title: A fuzzy multi-objective model for a cellular manufacturing system with layout designing in a dynamic condition

Authors: Ali Mohtashami; Alireza Alinezhad; Amir Hossein Niknamfar

Addresses: Department of Industrial Management, Qazvin Branch, Islamic Azad University, Qazvin, Iran ' Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering,Qazvin Branch, Islamic Azad University, Qazvin, Iran ' Young Researchers and Elite Club, Qazvin Branch, Islamic Azad University, Qazvin, Iran

Abstract: Cellular manufacturing system (CMS) plays a remarkably significant role in modern production systems. This paper presents a novel and practical fuzzy multi-objective mathematical model for a CMS in a dynamic condition considering the flexibility in allocating machines. The proposed model seeks to determine the best layout design in each production period. Two conflicting objectives are considered including minimising the cost of manufacturing system due to the amount of production loss caused by waste, as well as minimising the variance of fuzzy costs. Due to the complexity of the problem, non-dominate sorting genetic algorithm-II and multi-objective particle swarm optimisation algorithm are designed to solve the model and to obtain the effective solutions. In order to demonstrate the efficiency of the algorithms and to choose the premier algorithm, both algorithms are evaluated in several A fuzzy multi-objective model for a cellular manufacturing system 515 random problems and then compared based on the existing measurement indicators. Then, the algorithms are tuned to solve the problem, based on which their performances are analysed statistically. The applicability of the proposed approach and the solution methodologies are demonstrated as well.

Keywords: cellular manufacturing system; fuzzy theory; MOPSO algorithm; NSGA-II algorithm.

DOI: 10.1504/IJISE.2020.106086

International Journal of Industrial and Systems Engineering, 2020 Vol.34 No.4, pp.514 - 543

Received: 04 Dec 2017
Accepted: 14 Sep 2018

Published online: 19 Mar 2020 *

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