Speed Optimization in Bulk Carriers: A Weather-Sensitive Approach for Reducing Fuel Consumption

Abstract

The maritime industry faces the critical challenge of achieving net-zero greenhouse gas emissions by 2050, as mandated by the International Maritime Organization. This study introduces a novel speed optimization model, designed specifically for bulk carriers operating between two ports. Unlike conventional models that often assume static weather conditions, the proposed model incorporated variable weather conditions at different times of arrivals, as quantified by the Beaufort number (BN) and weather direction, for each leg of the voyage. Fuel consumption was estimated by applying regression to historical voyage data. This study employed a genetic algorithm (GA) to optimize vessel speed and thereby minimize fuel consumption. The model was tested by using different fuel consumption response curves relative to different BNs and weather directions. The results indicated that the proposed method could effectively reduce fuel consumption compared with the historical sailing mode by around 3%. The optimal speed recommendation indicated that the vessel should operate at a higher speed in circumstances associated with relatively low fuel consumption, such as lower BN and following sea conditions. Nonetheless, if it is possible to attain relatively low fuel consumption by adjusting the speed, the GA assesses the viability of this course of action. The study suggests that the predictive accuracy could be further enhanced by incorporating more granular, validated voyage data in future research.