{'fraction_non_alphanumeric': 0.02368421052631579, 'fraction_numerical': 0.0, 'mean_word_length': 5.341666666666667, '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}}
Factorial representation in scheduling problems

For problems considered difficult to solve systematically, various search methods have been developed. Such methods include Genetic Algorithms (GAs), Simulated Annealing (SA) and Taboo Search (TS). In this study, we examined applications of GA for scheduling problems, and proposed a factorial representation as the chromosome expression. The advantage of using factorial numbers to express permutations is that lethal genes are not produced by crossover or mutation. As a result of numerical experiments, the search ability of the proposed method was greater than the methods using permutations in GA. In particular, the search ability was superior to SA or TS when the average work time was different by work.