An integrated container terminal scheduling problem with different-berth sizes via multiobjective hydrologic cycle optimization

Huifen Zhong, Zhaotong Lian, Bowen Xue, Ben Niu, Rong Qu, Tianwei Zhou

Research output: Contribution to journalArticlepeer-review

Abstract

Integrated berth and quay crane allocation problem (BQCAP) are two essential seaside operational problems in container terminal scheduling. Most existing works consider only one objective on operation and partition of quay into berths of the same lengths. In this study, BQCAP is modeled in a multiobjective setting that aims to minimize total equipment used and overall operational time and the quay is partitioned into berths of different lengths, to make the model practical in the real-world and complex quay layout setting. To solve the new BQCAP efficiently, a multiobjective hydrologic cycle optimization algorithm is devised considering problem characteristics and historical Pareto-optimal solutions. Specifically, the quay crane of the large vessel in all Pareto-optimal solutions is rearranged to increase the chance of finding a good solution. Besides, worse solutions are probabilistic retained to maintain diversity. The proposed algorithm is applied to a real-world terminal scheduling problem with different sizes from a container terminal company. Experimental results show that our algorithm generally outperforms the other well-known peer algorithms and its variants on solving BQCAP, especially in finding the Pareto-optimal solutions range.
Original languageEnglish
Pages (from-to)11909-11925
Number of pages17
JournalInternational Journal of Intelligent Systems
Volume37
Issue number12
DOIs
Publication statusPublished - Jan 2022

Keywords

  • evolutionary computing algorithm
  • hydrologic cycle optimization
  • integrated berth and quay crane allocation problem
  • multiobjective optimization
  • scheduling

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