{'fraction_non_alphanumeric': 0.025590551181102362, 'fraction_numerical': 0.0, 'mean_word_length': 4.947368421052632, '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}}
Genetic Algorithm-Based Optimization Approach for an Uncapacitated Single Allocation P-hub Center Problem with more realistic cost structure

A p-hub center network design problem is definition of some nodes as hubs and allocation of non-hub nodes to them wherein the maximum travel times between any pair of nodes is minimized. The distinctive feature of this study is proposing a new mathematical formulation for modeling costs in a p-hub center problem. Here, instead of considering costs as a linear function of distance, for the first time, we formulate costs as a summation of different parts: fixed cost, Health, Safety and Environment (HSE) cost, energy cost and personnel cost. Such integrated model results in a hard-to-solve nonlinear formulation. To validate the proposed model, a small scale problem instance of CAB dataset solved by LINGO software. Because of inability to solve bigger problems, we prepared a Genetic Algorithm (GA) by MATLAB software to solve complete problems of CAB and AP datasets.