A Cubic q‐Rung Orthopair Fuzzy Decision Framework for Offshore Wind Farm Site Selection Using Entropy Weighting and Ideal‐Solution‐Based Ranking

ABSTRACT In offshore wind power development, offshore wind farm siting (OWFS) is a crucial yet complex decision process, often compromised by expert linguistic ambiguity, multidimensional expert evaluation and conflicting criteria. To tackle these challenges, this study proposes an integrated multicriteria group decision‐making (MCGDM) framework that integrates the entropy weight method (EWM) with the cubic q‐rung orthopair fuzzy extension of TOPSIS (Cq‐ROF‐TOPSIS). First, a hierarchical evaluation system consisting of six main criteria and 22 subcriteria is established, grounded in literature research. A dual‐layer weighting scheme is implemented to determine criteria weights. Specifically, main criteria weights are elicited from expert scoring, whereas subcriteria weights are objectively computed via EWM. Subsequently, expert evaluations are quantified as Cq‐ROF numbers to construct individual Cq‐ROF decision matrices, which are then aggregated into a comprehensive decision matrix using the power average operator. During this stage, a dynamic mechanism is employed to calculate expert weights based on their mutual support degrees, thereby effectively minimizing the negative impacts of extreme or biased assessments. Finally, the Cq‐ROF‐TOPSIS model ranks alternative sites based on their closeness coefficients to the positive ideal solution. A case study demonstrates the effectiveness of the proposed framework, while stability analysis across values confirms its robustness.