{'fraction_non_alphanumeric': 0.018973214285714284, 'fraction_numerical': 0.0, 'mean_word_length': 5.6940298507462686, '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}}
Mission Planning of MAV/UAV Cooperative Combat based on Improved Genetic Algorithm

Manned/unmanned aerial vehicles (MAV/UAV) cooperative combat mission planning is an extremely complex decision-making and optimizing problem. The purpose of this is to maximize the overall combat benefit with minimum cost by allocating reasonable targets for different types of aircraft, and proposing rough path planning for coordinated combat formations. Based on the background of OODA integrated combat cycle, this paper establishes the combination optimization model of MAV/UAV cooperative combat, and solves the problems of heterogeneity and resource limitation of MAV/UAV cooperative combat task planning by improving multi genotype genetic algorithm. Finally, the feasibility and effectiveness of this method are proved by the combat mission of MAV/UAV formation cooperating against ground fixed targets.