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All Journal KAPAL Jurnal Ilmu Pengetahuan dan Teknologi Kelautan
Stevanus Fransiscus Sahusilawahe
Suaka Bahari Maritime Academy Cirebon
Earth & Planetary Sciences

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Modeling Shipping Route Optimization Based On Seasonal Ocean Current Variability Using The Ant Colony Algorithm Brachmantiyo Rachman Pratama; Erik Sugianto; Supartono Supartono; Stevanus Fransiscus Sahusilawahe
Kapal: Jurnal Ilmu Pengetahuan dan Teknologi Kelautan Vol 23, No 2 (2026): June
Publisher : Department of Naval Architecture - Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/kapal.v23i2.82341

Abstract

Indonesia possesses dense and strategic shipping lanes, where seasonal ocean currents in the Java Sea frequently impact vessel transit times. On palm-oil shipping routes from Kumai to various ports in Java, route efficiency is paramount as fuel constitutes the largest operational expense. Due to the variability of ocean currents, conventional routes are not always the most efficient choice. This study utilizes 2024 ocean-current data from the Copernicus Marine Service alongside the technical specifications of the MT Nusaniwe to calculate effective speed, travel time, and fuel consumption. The Ant Colony Optimization (ACO) algorithm is applied to evaluate alternative route combinations under varying seasonal current conditions. The methodology encompasses current analysis, effective-speed formulation, fuel-consumption modeling, and route-optimization simulations for both the northwest and southeast monsoon seasons. Previous literature has not integrated ACO with seasonal oceanographic data for route optimization, which defines the research gap addressed herein. The results demonstrate that ACO-based routes integrated with oceanographic data outperform conventional routes, achieving significant reductions in transit time and fuel consumption. Consequently, this model proves that leveraging seasonal currents can enhance vessel operational efficiency and support data-driven voyage planning.
Co-Authors Brachmantiyo Rachman Pratama Erik Sugianto Supartono Supartono