A Hybrid Meta-Heuristic Approach for Solving Single-Vessel Quay Crane Scheduling with Double-Cycling

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Detaylı Bibliyografya
Yayımlandı:	Journal of Marine Science and Engineering vol. 13, no. 2 (2025), p. 371
Yazar:	Eldemir, Fahrettin
Diğer Yazarlar:	Taner, Mustafa Egemen
Baskı/Yayın Bilgisi:	MDPI AG
Konular:	Quays Containers Integer programming Ports Cranes Optimization techniques Decision support systems Automation Statistical analysis Transport buildings, stations and terminals Ant colony optimization Heuristic Heuristic methods Efficiency Scheduling Simulation Genetic algorithms Decision making Problem solving Algorithms Logistics Statistical methods Completion time Adaptive search techniques Cranes & hoists Economic
Online Erişim:	Citation/Abstract Full Text + Graphics Full Text - PDF
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Diğer Bilgiler
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.
ISSN:	2077-1312
DOI:	10.3390/jmse13020371
Kaynak:	Engineering Database