A Comprehensive Approach to Account for Weather Uncertainties in Ship Route Optimization

Vettor, Roberto; Bergamini, Giovanni; Soares, C. Guedes

doi:10.3390/jmse9121434

Cited by 9 publications

(1 citation statement)

References 26 publications

(27 reference statements)

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“…In this study, the traditional GA from the pymoo package, developed by Blank and Deb [25], was used to address this problem using Python. Given the potential for daily variations in weather forecasts for each leg of the journey, accuracy is maximized when the optimization procedure is executed at regular intervals [26][27][28]. GA is widely used in a variety of fields [29][30][31][32][33].…”

Section: Optimization Algorithmmentioning

confidence: 99%

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

Shih,

Tzeng,

Cheng

et al. 2023

JMSE

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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.

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