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12 November 2024 Research on optimal vehicle path algorithm based on improved ant colony algorithm
Jun Nie, Weiqing Xie, Hang Zhang, Wen Zhang
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Proceedings Volume 13395, International Conference on Optics, Electronics, and Communication Engineering (OECE 2024) ; 133952E (2024) https://doi.org/10.1117/12.3049001
Event: International Conference on Optics, Electronics, and Communication Engineering, 2024, Wuhan, China
Abstract
At present, vehicle routing optimization has become the key to improving logistics efficiency and reducing costs. This article proposes an improved ant colony algorithm to address the limitations of traditional ant colony algorithms in the optimal path problem for vehicles. The core of this study is to improve the pheromone update model of ant colony algorithm and validate it by constructing an experimental environment. The improved ant colony algorithm proposed in this article has significant performance improvements in solving vehicle path optimization problems, and is feasible and superior in practical applications, especially in terms of search efficiency. This algorithm provides a new perspective for future research directions.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Jun Nie, Weiqing Xie, Hang Zhang, and Wen Zhang "Research on optimal vehicle path algorithm based on improved ant colony algorithm", Proc. SPIE 13395, International Conference on Optics, Electronics, and Communication Engineering (OECE 2024) , 133952E (12 November 2024); https://doi.org/10.1117/12.3049001
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KEYWORDS
Transportation
Mathematical optimization
Roads
Detection and tracking algorithms
Chemical elements
Computer simulations
Mathematical modeling
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