{'fraction_non_alphanumeric': 0.0264797507788162, 'fraction_numerical': 0.0, 'mean_word_length': 5.628865979381444, '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}}
Economic dispatch solution using a genetic algorithm based on arithmetic crossover

In this paper, a new genetic approach based on arithmetic crossover for solving the economic dispatch problem is proposed. Elitism, arithmetic crossover and mutation are used in the genetic algorithm to generate successive sets of possible operating policies. The proposed technique improves the quality of the solution. The new genetic approach is compared with an improved Hopfield NN approach (IHN), a fuzzy logic controlled genetic algorithm (FLCGA), an advance engineered-conditioning genetic approach (AECGA) and an advance Hopfield NN approach (AHNN).