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

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Bibliografiske detaljer
Udgivet i:	Journal of Marine Science and Engineering vol. 13, no. 2 (2025), p. 371
Hovedforfatter:	Eldemir, Fahrettin
Andre forfattere:	Taner, Mustafa Egemen
Udgivet:	MDPI AG
Fag:	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
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Beskrivelse
Resumen:	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
Fuente:	Engineering Database