research article

DEVELOPMENT OF A FUZZY-BASED DECISION SUPPORT SYSTEM FOR SUSTAINABLE TRACTOR SELECTION IN GREEN PORTS

Abstract

Tractors play a critical role in the operational processes of green ports. The primary objective of this study is to develop a decision support system (DSS) for the selection of tractors suitable for green port operations. In this context, a hybrid multi-criteria decision-making (MCDM) approach based on fuzzy logic—namely the FF-Hamacher-CIMAS-LODECI-RADAR (Fermatean Fuzzy–Hamacher-Criteria Importance Assessment-Logarithmic Decomposition of Criteria Importance- Ranking based on the Distances and Range) hybrid method is proposed. This hybrid model enables the simultaneous integration of both quantitative and qualitative criteria into the decision-making process. Expert weight vectors are determined using Fermatean fuzzy sets, while the overall criteria weight vector is constructed through a combination of subjective (FF-Hamacher-CIMAS) and objective (FF-Hamacher-LODECI) weighting techniques. The performance ranking of tractor alternatives is obtained using the RADAR method. The proposed methodology was applied to a tractor selection problem for a green port in Türkiye. The decision model was established based on the evaluations of ten experts, involving eight criteria (two quantitative and six qualitative) and five alternative tractors. According to the results of the case study, Towing Capacity emerged as the most influential criterion. Among the alternatives, the MAFI T 230e tractor demonstrated the highest performance. The robustness of the proposed hybrid method was supported through three sensitivity analysis scenarios. Additionally, comparative analyses revealed a high level of consistency in the results, confirming the reliability of the method. Based on the findings, practical implications and recommendations were provided to support decision-making processes in green port operations

    Similar works