{'fraction_non_alphanumeric': 0.02252252252252252, 'fraction_numerical': 0.0011261261261261261, 'mean_word_length': 5.5851851851851855, '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}}
Heterogeneous Feature Ant Colony Optimization Algorithm Based on Effective Vertexes of Obstacles

In this paper, path planning of automated guided vehicle (AGV) in complex environment was investigated. A heterogeneous feature ant colony optimization algorithm based on effective vertexes of obstacles (EV-HFACO) is proposed to solve the problem of poor convergence and local optimum. Firstly, the grid method based on effective vertexes of obstacles played a very positive role as the method of environment modeling. Then, the different state rules which incorporate perspective-taking ability were designed. In addition, a new pheromone update mechanism was employed to balance the rapidity and randomness. Finally, some numerical results of simulation indicated the effectiveness of the proposed algorithms which could outperform that of popular SoSACO-v2” Sci-ACO and HHACO algorithms.