University Of Tasmania

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Development of a two-stage ship fuel consumption prediction and reduction model for a dry bulk ship

journal contribution
posted on 2023-05-20, 14:03 authored by Yan, R, Wang, S, Yuquan Du
Shipping industry is the backbone of global trade. However, the large quantities of greenhouse gas emissions from shipping, such as carbon dioxide (CO2), cannot be ignored. In order to comply with the international environmental regulations as well as to increase commercial profits, shipping companies have stronger motivations to improve ship energy efficiency. In this study, a two-stage ship fuel consumption prediction and reduction model is proposed for a dry bulk ship. At the first stage, a fuel consumption prediction model based on random forest regressor is proposed and validated. The prediction model takes into account ship sailing speed, total cargo weight, and sea and weather conditions and then predicts hourly fuel consumption of the main engine. The mean absolute percentage error of the random forest regressor is 7.91%. At the second stage, a speed optimization model is developed based on the prediction model proposed at the first stage while guaranteeing the estimated arrival time to the destination port. Numerical experiment on two consecutive-8-day voyages shows that the proposed model can reduce ship fuel consumption by 2–7%. The reduction in ship fuel consumption will also lead to lower CO2 emissions.


Publication title

Transportation Research Part E: Logistics and Transportation Review



Article number









Australian Maritime College


Pergamon-Elsevier Science Ltd

Place of publication

The Boulevard, Langford Lane, Kidlington, Oxford, England, Ox5 1Gb

Rights statement

© 2020 Elsevier Ltd. All rights reserved.

Repository Status

  • Restricted

Socio-economic Objectives

International sea freight transport (excl. live animals, food products and liquefied gas)