Two-stage meta-heuristic algorithm for parallel machine scheduling with additional resource input in shipyard manufacturing

Soonkyo Lee, Taesu Cheong, Seokhyun Chung

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Development of an efficient workspace scheduling algorithm for shipyard manufacturing has become more crucial as the modern smart factory technologies burgeon. Because shipyard manufacturing is generally conducted on a large scale, making workspace scheduling decisions is not a trivial mission. In particular, one needs to consider several factors (due date, resource limitation in the workspace, etc.) in order to efficiently schedule block processing in the workspace. A commonly used strategy is to input additional resources into a workspace to shorten the total production time. By implementing this strategy, one can curtail the total production time, which can later result in significant cost reductions in shipyard manufacturing. In this study, we tackle the workspace scheduling in shipyard manufacturing problem by taking the additional resource input strategy into account. This problem can be considered as a class of the parallel machine scheduling problem. We present a mixed integer programming model for the addressed problem and develop an efficient meta-heuristic algorithm. The proposed algorithm is composed of two stages: (i) a genetic algorithm enhanced by an ordering-based heuristic scheduling and (ii) a tabu-search algorithm for local search that considers the additional resources input method.

Original languageEnglish
Title of host publication4th North American IEOM Conference. IEOM 2019
PublisherIEOM Society
Number of pages2
ISBN (Print)9781532359507
Publication statusPublished - 2019 Jan 1
Event4th North American IEOM Conference. IEOM 2019 - Toronto, Canada
Duration: 2019 Oct 232019 Oct 25

Publication series

NameProceedings of the International Conference on Industrial Engineering and Operations Management
ISSN (Electronic)2169-8767


Conference4th North American IEOM Conference. IEOM 2019


  • Genetic algorithm
  • Parallel machine scheduling
  • Shipyard manufacturing
  • Tabu search

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering


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