Optimization of power material distribution route based on hybrid ant colony algorithm

Liang Feng; Tian Nan

doi:10.1117/12.3026070

6 May 2024 Optimization of power material distribution route based on hybrid ant colony algorithm

Liang Feng, Tian Nan

Proceedings Volume 13161, Fourth International Conference on Telecommunications, Optics, and Computer Science (TOCS 2023); 131610P (2024) https://doi.org/10.1117/12.3026070
Event: Fourth International Conference on Telecommunications, Optics and Computer Science (TOCS 2023), 2023, Xi’an, China

Abstract

Aiming at the problem of how to carry out efficient distribution of electric power materials, the optimization model of distribution route for electric power materials considering time window is designed. The model takes the minimum distance travelled by vehicles as the objective, and at the same time considers the constraints such as vehicle load and time window of each demand node, so as to make the model more in line with the demand of electric power material distribution. In order to improve the solving ability of the optimization model, the idea of Genetic Algorithm (GA) and Simulated Annealing Algorithm (SA) are introduced into the Ant Colony Algorithm (ACO) to form the Hybrid ACO algorithm. The feasibility of the algorithm is verified by choosing the international common examples. The results show that the travelling distance of the optimal route obtained by the hybrid ACO algorithm is significantly shorter than that of the optimal route obtained by the GA algorithm. Therefore, the proposed algorithm can provide theoretical references for the decision-making of electric power material distribution.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Liang Feng and Tian Nan "Optimization of power material distribution route based on hybrid ant colony algorithm", Proc. SPIE 13161, Fourth International Conference on Telecommunications, Optics, and Computer Science (TOCS 2023), 131610P (6 May 2024); https://doi.org/10.1117/12.3026070

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