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

Author

Listed:
  • Parames Chutima
  • Watcharawit Tanontong

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.

Suggested Citation

  • Parames Chutima & Watcharawit Tanontong, 2019. "Two-sided assembly line car sequencing with a fuzzy adaptive extended coincidence algorithm," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 32(1), pages 71-102.
    • Handle: RePEc:ids:ijisen:v:32:y:2019:i:1:p:71-102
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