Title: Two-sided assembly line car sequencing with a fuzzy adaptive extended coincidence algorithm

Authors: Parames Chutima; Watcharawit Tanontong

Addresses: Regional Centre for Manufacturing Systems Engineering, Chulalongkorn University, Bangkok 10330, Thailand; Department of Industrial Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand ' Department of Industrial Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand

Abstract: The car sequencing problem is a constraint satisfaction problem that has attracted the attention of academia and practitioners for many years now. In this paper, the industrial version of the car sequencing problem is extended to reflect more real operations in practice by using a two-sided assembly line instead of classical single-sided one. The fuzzy adaptive extended coincidence algorithm (COIN-F) is developed to optimise the multi-objective car sequencing problem in a Pareto sense. The relative performance of COIN-F is compared against COIN-E, NSGA-II and DPSO. Experimental results demonstrate the effectiveness of COIN-F over the contestant algorithms, especially in the search for the approximate true-Pareto frontier.

Keywords: car sequencing; two-sided assembly line; coincidence algorithm COIN; fuzzy adaptive.

DOI: 10.1504/IJISE.2019.099777

International Journal of Industrial and Systems Engineering, 2019 Vol.32 No.1, pp.71 - 102

Received: 23 Oct 2016
Accepted: 10 Sep 2017
Published online: 22 May 2019 *

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