{'fraction_non_alphanumeric': 0.01665278934221482, 'fraction_numerical': 0.0, 'mean_word_length': 5.868571428571428, '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}}
Facility layout problem: an approach based on a group decision-making system and psychoclonal algorithm

The facility layout problem is modeled for a multi-person, multi-criteria and multi-preference scenario. Various preference modes have been transformed into a Multiplicative Preference Relationship, as it is easy to aggregate the group preferences into a single preference. To obtain more reliable knowledge, an Ordered Weighted Averaging operator is used for the aggregation of the information obtained by decision makers. To search for the optimum solution through systematic reasoning, an evolutionary optimization-based technique, namely a Psychoclonal Algorithm, is proposed to solve a layout design problem considering the dynamic characteristics and operational constraints of the system. During an extensive computational experiment on a benchmark dataset adopted from the literature, it was observed that the proposed Psychoclonal Algorithm outperformed other methodologies. Further, we considered a test bed comprising a few problems with randomly generated datasets and solved them using the proposed algorithm and traditional algorithms for the validation of our solution methodology.