{'fraction_non_alphanumeric': 0.017837235228539576, 'fraction_numerical': 0.0, 'mean_word_length': 5.27972027972028, '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 Multimodal Particle Swarm Optimization Algorithm Based on Greedy Algorithm

A new multimodal particle swarm optimization algorithm based on greedy algorithm (GAPSO) is proposed in this paper. A ring topology is employed in each niche instead of a fully connected topology in GAPSO. More importantly, GAPSO does not depend on any niching parameter, which improves its effectiveness and efficiency greatly. A range of standard test functions are employed to test this proposed algorithm's performance. Experimental results demonstrate that GAPSO performs as well as existed optimization algorithms, and needs smaller number of evaluations to locate all the global optima for simple problems. For complex problems, GAPSO can achieve better and more consistent performance, and can locate more global optima than SPSO, ANPSO and rpso, which makes it possible to be widely used in the real world.