OICC Press Fuzzy Optimization and Modeling Journal (FOMJ) 2676-7007 5 2 2024 07 03 A Compromise Solution Approach for Fuzzy Data Envelopment Analysis: A Case of the Efficiency Prediction 32 52 10.71808/FOMJ.2024.1002618 EN Nam Hyok Kim School of Economics and Management, University of Science & Technology Beijing, Beijing 100083, PR China Feng He School of Economics and Management, University of Science & Technology Beijing, Beijing 100083, PR China Kwang-Chol Ri Faculty of Information Science, Kim Il Sung University, Pyongyang, DPR Korea Son-Il Kwak Faculty of Information Science, Kim Il Sung University, Pyongyang, DPR Korea Journal Article 2024 07 03 The data envelopment analysis (DEA) a data-oriented approach for evaluating the relative performance of decision-making units (DMUs). The traditional DEA applies only to crisp data, whereas the data collected in the real world may be ambiguous and imprecise. The fuzzy DEA is an extension of the DEA using the fuzzy variable to deal with uncertain or imprecise data. This paper proposes two new fuzzy arithmetic-based DEA models with dynamic weights and common weights, formulated as multiple objective decision-making (MODM), and proposed models are represented as the linear programs providing the compromise solutions. The numerical experiment is illustrated to examine the validity of the proposed models, and the experiment shows that the proposed models give better results than other models. The proposed fuzzy DEA models are applied to predict the energy efficiency of 40 iron and steel enterprises in China.