An integrated container terminal scheduling problem with different‐berth sizes via multiobjective hydrologic cycle optimization. Issue 12 (16th September 2022)

• Record Type: Journal Article
• Authors: Zhong, Huifen; Lian, Zhaotong; Xue, Bowen; Niu, Ben; Qu, Rong; Zhou, Tianwei
• Is Part Of: International journal of intelligent systems. Volume 37:Issue 12(2022)
• Page Start: 11909
• Page End: 11925
• Publication Date: 2022-09-16
• Subjects: evolutionary computing algorithm -- hydrologic cycle optimization -- integrated berth and quay crane allocation problem -- multiobjective optimization -- scheduling; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; 006.3
• DOI: 10.1002/int.23069
• Languages: English
• ISSNs: 0884-8173

Abstract

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.