{'fraction_non_alphanumeric': 0.016877637130801686, 'fraction_numerical': 0.0, 'mean_word_length': 5.683098591549296, '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}}
A Hybrid Fuzzy Approach to Fuzzy Multi-Attribute Group Decision-Making

The paper investigates fuzzy multi-attribute group decision-making (FMAGDM) problems. The important weights of the attributes and the ratings of the alternatives with respect to each attribute provided by multiple decision-makers are described by the linguistic variables expressed in triangular fuzzy numbers or trapezoidal fuzzy numbers. A hybrid fuzzy approach is proposed, which assesses each alternative in terms of distance measure calculated by a modified VIKOR method as well as similarity measure calculated by a modified gray relational analysis (GRA) method, to the positive ideal alternative and the negative ideal alternative. A new relative closeness coefficient is established to rank alternatives by aggregating the distance and the similarity measures. Two numerical examples for reverse logistics applications are presented to illustrate the proposed method.