This research demonstrates how the TOPSIS method and agents improve ship-type decision-making, indicating a need for better performance metrics.
This study quantifies ship-type performance indicators by training intelligent agents to evaluate and score vessels. The Analytic Hierarchy Process (AHP) is then applied to assess the internal consistency of the collected data, ensuring its authenticity and validity. Subsequently, the entropy weight method is employed to objectively determine the significance of each indicator in ship-type decision-making. Finally, COSCO (China COSCO Shipping Corporation Limited) Shipping’s capacity gap reflects the results of the methodology: the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) technique ranks all feasible ship-type combinations, presenting their relative merits through quantitative results. A standardized grading system is further proposed to evaluate these combinations systematically. Ultimately, the 10 most suitable solutions are identified—none achieving the theoretical maximum rating of Grade 10—demonstrating room for improvement in vessel performance.
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Han et al. (2025) studied this question.
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