Cross‐entropy is a useful tool for quantifying the divergence between systems. In this paper, we develop an interval‐valued q‐rung orthopair fuzzy cross‐entropy measure. Subsequently, the satisfaction‐based cross‐entropy (SCE) is derived from the compromise rule, integrating decision‐makers’ risk preferences to enhance rationality. In addition, we introduce a novel boundary cross‐entropy (BCE) metric specifically designed for interval‐valued q‐rung orthopair fuzzy numbers (IVq‐ROFNs). Building on these measures, we propose a cross‐entropy‐based modified multiattributive border approximation area comparison (MABAC) method. One of the prominent components of the developed method is to determine the weights of attributes depending on the coefficient of variation method and the cross‐entropy, and the other is to develop a new SCE‐based model to determine the weights of experts. Moreover, for the modified MABAC method, the values of the boundary approximation area (BAA) matrix are obtained by the q‐RIVOFWG operator, and the BCE values between alternatives are derived from the BAA matrix. The final decision outcomes are determined based on the total BCE values. The proposed MABAC group decision‐making (GDM) method is verified through a course learning evaluation case study. Its practicability and effectiveness are demonstrated via comparative analysis, sensitivity analysis, and time complexity analysis.
Wan et al. (Thu,) studied this question.
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