Review of the Decision Support Methods Used in Optimizing Ship Hulls towards Improving Energy Efficiency

This paper presents a review of the different methods and techniques used to optimize ship hulls over last six years (2017–2022). shows percentages reduction in resistance, thus fuel consumption, improve ships’ energy efficiency, towards achieving goal maritime decarbonization. Operational research machine learning are common decision support find optimal solution. covers four areas hulls, including hull form, structure, cleaning lubrication. In each area research, several computer programs used, depending on study’s complexity objective. It has been found that no specific method is considered optimum, while combination can achieve more accurate results. Most work focused concept stage design, operational conditions recently taken place, an improvement efficiency. The finding this study contributes mapping scientific knowledge technology identifying relevant topic areas, recognizing gaps opportunities. also helps present holistic approaches future supporting realistic solutions sustainability.