A Hybrid Meta-Heuristic Approach for Solving Single-Vessel Quay Crane Scheduling with Double-Cycling
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Tarih
2025
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Mdpi
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
The escalating global demand for containerized cargo has intensified pressure on container terminals, which serve as vital nodes in maritime logistics. This study aims to enhance operational efficiency in non-automated container terminals by examining two meta-heuristic approaches-Ant Colony Optimization (ACO) and a hybrid Greedy Randomized Adaptive Search Procedure (GRASP)-Genetic Algorithm (GA)-for quay crane scheduling. Their performance is benchmarked across various problem scales, with process completion time serving as the primary metric. Based on these findings, the most effective approach is integrated into a newly developed Decision Support System (DSS) to streamline practical implementation. Statistical analyses confirm the robustness of both methods, underscoring how meta-heuristics combined with a DSS can optimize quay crane utilization, bolster maritime logistics, and ultimately boost terminal productivity.
Açıklama
Anahtar Kelimeler
port management, maritime transport, container terminals, quay crane scheduling, meta-heuristics, GRASP-GA, ant colony optimization, decision support system
Kaynak
Journal of Marine Science and Engineering
WoS Q Değeri
Q1
Scopus Q Değeri
Q2
Cilt
13
Sayı
2
