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

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Vydáno v:Journal of Marine Science and Engineering vol. 13, no. 2 (2025), p. 371
Hlavní autor: Eldemir, Fahrettin
Další autoři: Taner, Mustafa Egemen
Vydáno:
MDPI AG
Témata:
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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Abstrakt: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
Zdroj:Engineering Database