Mr. Jun Wan Profile

Jun Wan

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Proceedings Article | 20 February 2024 Paper

Based on the logistics and transportation planning and simulation in the field of intelligent transportation

Jun Wan, Jingyi Wang

Proceedings Volume 13064, 130643T (2024) https://doi.org/10.1117/12.3015708

KEYWORDS: Transportation, Roads, Safety, Intelligence systems, Modeling, Intelligent sensors, Data modeling, Telecommunications, Intelligent sensor systems, Computer simulations

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Intelligent transportation system plays an important role in the field of logistics transportation, which can improve the efficiency of logistics transportation, reduce costs and reduce traffic congestion. Logistics transportation planning and simulation is a key problem in the field of intelligent transportation. It can help logistics enterprises to carry out reasonable path planning and resource allocation, predict the possible problems in the transportation process in advance, and optimize the transportation scheme to improve the transportation efficiency. Based on the logistics and transportation planning and simulation in the field of intelligent transportation, this paper studies how to optimize the path selection, resource scheduling and transportation planning arrangement in the process of logistics and transportation through the modeling and simulation of the existing logistics and transportation system. The experimental results of this paper show that the logistics simulation system based on the field of intelligent transportation has advantages over the traditional logistics system in terms of transportation time, cost and safety indicators. Specifically, the average transportation time of this system is 8.5 hours, which is shorter than 10.5 hours of the traditional logistics system; the average cost is 4280 yuan, lower than 5000 yuan of the traditional logistics system, and the average safety index is 93.3%, which is higher than 88.5% of the traditional logistics system. It shows that the logistics simulation system based on the field of intelligent transportation has potential and feasibility in logistics transportation, which is expected to promote the development of logistics industry and improve the efficiency of logistics transportation.

Proceedings Article | 14 February 2024 Open Access

Optimization analysis of cold chain logistics network structure based on genetic algorithm

Jun Wan, Chengwu Zheng

Proceedings Volume 13018, 130181Z (2024) https://doi.org/10.1117/12.3024190

KEYWORDS: Transportation, Genetic algorithms, Mathematical optimization, Safety, Analytical research, Temperature control, Information technology, Genetics, Binary data, Temperature metrology

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This paper presents an optimization analysis of the cold chain logistics network structure based on genetic algorithms. Firstly, the theoretical overview of the cold chain logistics network is introduced, including the concept, characteristics, and operation process of cold chain logistics, as well as the functional effects of logistics networks. Then, the structure of the cold chain logistics network is studied, including its composition and link analysis, and the formation mechanism of the cold chain logistics network is discussed. Subsequently, the genetic algorithm and its basic ideas and solution steps are explained in detail, and a genetic algorithm-based optimization model for the layout of cold chain logistics network nodes is constructed. The feasibility and effectiveness of the model are verified through case analysis. Finally, the research results of the paper are summarized, emphasizing the importance of optimizing the structure of the cold chain logistics network to improve operational efficiency. The research findings of this paper are of great significance for promoting the development of the cold chain logistics industry.

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