{'fraction_non_alphanumeric': 0.007518796992481203, 'fraction_numerical': 0.0, 'mean_word_length': 5.443548387096774, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Data Envelopment Analysis with Common Weights in a Fuzzy Environment

This work considers providing a common base for measuring the relative efficiency of a group of homogeneous decision making units in a fuzzy environment. The principle of compromise of the technique for order preference by similarity ideal solution is employed for solving the data envelopment analysis model with fuzzy objectives and constraints. An algorithm with the entropic regularization implementation for finding the compromise solution of the fuzzy data envelopment analysis model is developed. An illustrative example verifying the idea of this paper is provided. The contribution of this work is represented by the improvement of the discriminatory power of the fuzzy DEA, gained through the common weight evaluation.