Paper
7 December 2023 Solve the optimal path planning of material distribution in workshop with time window
Lihui Gao, Zhangcheng Guo
Author Affiliations +
Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 1294155 (2023) https://doi.org/10.1117/12.3011549
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China
Abstract
In recent years, the rapid development of the Internet industry and the rapid rise of the e-commerce industry have promoted the continuous development of the logistics industry, and ordinary workshops can no longer meet people's needs, and are gradually moving towards smart workshops. Among them, distribution as an important link of smart workshop logistics, scientific and reasonable planning of the workshop path in advance can not only achieve the on-time delivery of smart workshop materials, but most importantly, reduce the distribution cost. Vehicle route planning is one of the hot issues in current development and research. A workshop material distribution planning model with the objective function of minimizing total cost was established, and the model was solved by an improved ant colony algorithm. By improving the algorithm's state transfer rules and pheromone volatile factors as well as pheromone increment, the improved ant colony convergence speed was fast. The ability to jump out of local optimal is better. The improved algorithm is applied to vehicle routing problem with time window (VRPTW), and the workshop model is simulated by Solomon example, which proves that the total production cost is reduced. The total cost of production includes the number of routes and vehicles used, thus verifying the rationality of the algorithm.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Lihui Gao and Zhangcheng Guo "Solve the optimal path planning of material distribution in workshop with time window", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 1294155 (7 December 2023); https://doi.org/10.1117/12.3011549
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KEYWORDS
Industry

Mathematical modeling

Process modeling

Manufacturing

Materials processing

Modeling

Particle swarm optimization

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