Research on Route Optimization of RO-Ro Ship Based on Ant Colony Algorithm

This study is based on an ant colony algorithm for route optimisation of roll-on roll-off (RO-RO) vessels, aiming to minimise the total cost of RO-RO shipping routes. The model takes into account factors such as port berthing cost, fuel consumption and sailing time, and ensures the stability and efficiency of the optimisation results by adjusting the algorithm parameters such as pheromone initialisation, pheromone evaporation rate and ant colony size. The results of the study provide a practical solution for ro-ro ship route optimisation, which significantly reduces the operating costs and also provides key technical support for shipping companies to compete in the global market. In addition, the study demonstrates the potential of the optimisation model to reduce transport costs, improve shipping efficiency and reduce carbon emissions, providing an effective technical support for shipping companies in an increasingly competitive global market. Through this optimisation approach, shipping companies are able to better manage their route selection, resource allocation and operational processes, enhancing market competitiveness and promoting sustainable development of the shipping industry.

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Publication Details

Journal
Applied and Computational Engineering
Published
2024-12-06
DOI
https://doi.org/10.54254/2755-2721/2024.melb18117
Primary Topic
Maritime Ports and Logistics
Type
article
Field-Weighted Citation Impact
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article

Research on Route Optimization of RO-Ro Ship Based on Ant Colony Algorithm

Jialu Li
Applied and Computational Engineering
Maritime Ports and Logistics
article

Research on Route Optimization of RO-Ro Ship Based on Ant Colony Algorithm

Jialu Li
article en

Abstract

This study is based on an ant colony algorithm for route optimisation of roll-on roll-off (RO-RO) vessels, aiming to minimise the total cost of RO-RO shipping routes. The model takes into account factors such as port berthing cost, fuel consumption and sailing time, and ensures the stability and efficiency of the optimisation results by adjusting the algorithm parameters such as pheromone initialisation, pheromone evaporation rate and ant colony size. The results of the study provide a practical solution for ro-ro ship route optimisation, which significantly reduces the operating costs and also provides key technical support for shipping companies to compete in the global market. In addition, the study demonstrates the potential of the optimisation model to reduce transport costs, improve shipping efficiency and reduce carbon emissions, providing an effective technical support for shipping companies in an increasingly competitive global market. Through this optimisation approach, shipping companies are able to better manage their route selection, resource allocation and operational processes, enhancing market competitiveness and promoting sustainable development of the shipping industry.

Applied and Computational EngineeringVol. 110(1)
Shanghai Maritime University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 68%
Maritime Ports and Logistics
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