{'fraction_non_alphanumeric': 0.019011406844106463, 'fraction_numerical': 0.0, 'mean_word_length': 5.273809523809524, '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 new hybrid genetic algorithm for global minimax optimization

The minimax problem is one of the branches of multilevel programming, but unfortunately there is lack of efficient algorithms for it. The paper discusses the convergence of all alternative methods at the beginning, and then presents the SGA (simplex-genetic algorithm), which is an improved algorithm of GA for solving Stackelberg-Nash equilibrium. Examples are provided to illustrate that SGA is an efficient and universal means for solving the minimax problem.