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

Parames Chutima and Watcharawit Tanontong

International Journal of Industrial and Systems Engineering, 2019, vol. 32, issue 1, 71-102

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. (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijisen:v:32:y:2019:i:1:p:71-102

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