TY - GEN

T1 - Two-stage meta-heuristic algorithm for parallel machine scheduling with additional resource input in shipyard manufacturing

AU - Lee, Soonkyo

AU - Cheong, Taesu

AU - Chung, Seokhyun

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

AB - 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.

KW - Genetic algorithm

KW - Parallel machine scheduling

KW - Shipyard manufacturing

KW - Tabu search

UR - http://www.scopus.com/inward/record.url?scp=85079280331&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85079280331&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85079280331

SN - 9781532359507

T3 - Proceedings of the International Conference on Industrial Engineering and Operations Management

SP - 463

EP - 464

BT - 4th North American IEOM Conference. IEOM 2019

PB - IEOM Society

T2 - 4th North American IEOM Conference. IEOM 2019

Y2 - 23 October 2019 through 25 October 2019

ER -