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Shipyard Skid Sequence Optimization Using a Hybrid Genetic Algorithm

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2023, 28(12), pp.79-87
  • DOI : 10.9708/jksci.2023.28.12.079
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : November 13, 2023
  • Accepted : December 14, 2023
  • Published : December 29, 2023

Min-Jae Choi 1 Yung-Keun Kwon 1

1울산대학교

Accredited

ABSTRACT

In this paper, we propose a novel genetic algorithm to reduce the overall span time by optimizing the skid insertion sequence in the shipyard subassembly process. We represented a solution by a permutation of a set of skid ids and applied genetic operators suitable for such a representation. In addition, we combined the genetic algorithm and the existing heuristic algorithm called UniDev which is properly modified to improve the search performance. In particular, the slow skid search part in UniDev was changed to a greedy algorithm. Through extensive large-scaled simulations, it was observed that the span time of our method was stably minimized compared to Multi-Start search and a genetic algorithm combined with UniDev.

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.