Advancing towards indonesia's net zero emission goals: An in-depth multi-criteria decision making (MCDM) analysis of ship-loader operations in maritime transportation using interval type-2 fuzzy AHP and TOPSIS methods

Abstract

Efficient maritime logistics play a pivotal role in Indonesia's economic growth and development. Selecting an appropriate ship loader such as fixed, mobile, slew, parallel, shuttle, or tower types, is crucial for operational efficiency and environmental responsibility, particularly in port operations involving dry bulk cargo. The selection process requires the evaluation of multiple key performance indicators (KPIs), including loading rate, downtime, energy consumption, environmental impact, flexibility, capital expenditures, throughput volume, and loading accuracy. This study utilizes a structured multi-criteria decision-making framework that integrates the Interval Type-2 Fuzzy Analytical Hierarchy Process (IT2FAHP) with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to address decision-making challenges. By incorporating expert opinions from key maritime stakeholders including shipping companies, dry bulk terminals, shipping agent, and cargo shippers, this study accommodates subjective judgments and uncertainty in evaluating ship loader performance. The results indicate that loading rate is the most influential KPI, with a normalized weight of 41 %, and that the parallel ship loader is the most preferred alternative, with a closeness coefficient (CC) of 0.67. A sensitivity analysis validates the robustness of the model, with the fixed loader emerging as the most stable option across varying scenarios. While the IT2FAHP-TOPSIS method has been applied in other industrial contexts, this research presents its first systematic application within Indonesia’s maritime infrastructure. The findings offer both theoretical contributions and practical guidance for decision-makers in optimizing port operations while supporting broader sustainability objectives.