{'fraction_non_alphanumeric': 0.015355086372360844, 'fraction_numerical': 0.0, 'mean_word_length': 5.779220779220779, '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}}
Intelligent permuting and its optimization

In this paper genetic algorithm (GA) is developed and applied to the optimizing or rationalizing permutation problems with FMS scheduling as an example. Special methods of genetic coding for permutations, fitness function definitions, crossover and mutation operations are designed and tested. A novel catastrophe technique is suggested to rescue the GA procedure from evolution halt. The effectiveness of GA for permutation problems is identified by computational experiments.