Optimisation of maritime routes: An intelligent approach to logistics efficiency
Submitted: 2025-01-16
|Accepted: 2026-01-22
|Published: 2026-01-31
Copyright (c) 2026 Paola Alzate, Aura Guevara, Gustavo A. Isaza, Eliana M. Toro, Jorge A. Jaramillo-Garzón
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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Keywords:
Logistics clustering, Maritime route optimisation, Operational efficiency, Maritime transportation, Intelligent routing
Supporting agencies:
Universidad de Caldas
Abstract:
Efficient maritime route planning is pivotal for optimising global logistics operations in an increasingly competitive environment. This study aims to determine the optimal number of clusters among 90 georeferenced ports across six continents, minimizing distances and enhancing operational efficiency through advanced clustering techniques. Methods such as geographic k-means, Gaussian Mixture Models (GMM), and hierarchical clustering were implemented and evaluated using quality metrics like the Calinski-Harabasz, Silhouette, and Davies-Bouldin indices. The results identified 13 optimal clusters that reflect logical and geographically coherent segmentation, highlighting geographic k-means for its consistency and replicability. Additionally, integrating an intelligent routing model enabled the design of optimised routes within each cluster, reducing distances and maximizing logistical efficiency. The proposed methodology, developed in Python, demonstrates not only its applicability to maritime operations but also its potential for extrapolation to other contexts, showcasing robustness and relevance for global strategic planning. This approach represents a significant advancement in integrating clustering and optimisation techniques to enhance maritime supply chain management.
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