Prioritizing offshore wind development challenges in Taiwan under uncertainty: A fuzzy interval ranking approach

Offshore wind power (OWP) plays a pivotal role in Taiwan's energy transition, yet its large-scale deployment is hindered by complex technological, economic, institutional, environmental, and natural hazard challenges under substantial uncertainty. This study develops a Fuzzy Interval Ranking (FIR) framework to systematically prioritize these multifaceted challenges within a multi-criteria decision-making (MCDM) structure. Unlike traditional MCDM approaches, FIR directly processes interval-valued and fuzzy expert assessments without requiring normalization, pairwise comparisons, or predefined membership functions. The method integrates a quantized fuzzy scoring mechanism and possibility-based dominance relations to enhance computational efficiency, reduce sensitivity to extreme evaluations, and explicitly model uncertainty. Objective criterion weights are determined using Shannon's entropy method, and the robustness of FIR outcomes is validated through comparison with the Weighted Sum Model (WSM), the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and Analytic Hierarchy Process (AHP). Results from all methods consistently identify technological and economic challenges as the highest-priority factors, followed by policy and legislative barriers, while environmental constraints and natural disaster risks remain significant but comparatively lower in ranking. Sensitivity analyses further confirm that FIR rankings remain highly stable across varying weighting schemes and quantization parameters. The proposed framework offers a transparent, uncertainty-aware, and reproducible decision support tool for improving resource allocation and strategic planning in OWP. Beyond Taiwan, the methodology provides a transferable analytical foundation for countries confronting similar uncertainties in large-scale OWP deployment.