Logistics Distribution Route Optimization in Artificial Intelligence and Internet of Things Environment

Qianfei Liu

doi:10.31181/dmame7220241072

Authors

Qianfei Liu School Of Economics and Management, Jiaozuo University https://orcid.org/0000-0003-3580-3500

DOI:

https://doi.org/10.31181/dmame7220241072

Keywords:

Artificial intelligence, Internet of Things, Logistics distribution route optimization, Cost-benefit analysis

Abstract

With the increasing challenges facing the logistics industry, especially in meeting the growing demand for distribution efficiency and accuracy, the use of modern technology to optimize logistics distribution routes has become a key issue. This study explores the application of artificial intelligence (AI) and Internet of Things (IoT) technologies in the optimization of logistics distribution routes. The research first focused on collecting and processing logistics-related data, including historical delivery records, real-time traffic data, and cargo tracking information. Then, by building optimization models based on AI and IoT technologies, the study explores the potential of these technologies to improve logistics distribution efficiency and reduce costs. In addition, through cost-benefit analysis and discussion of challenge-coping strategies, this study not only verified the effectiveness of the proposed scheme in theory but also demonstrated its feasibility in practical application. Finally, the study presents implications for industry practice and recommendations for future research, emphasizing the importance of continuous technology evaluation and adaptation to market changes.

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References

Bhalotia, N., Kumar, M., Alameen, A., Mohapatra, H., & Kolhar, M. (2023). A Helping Hand to the Elderly: Securing Their Freedom through the HAIE Framework. Applied Sciences, 13(11), 6797. https://doi.org/10.3390/app13116797

Xin, L., Xu, P., & Manyi, G. (2022). Logistics distribution route optimization based on genetic algorithm. Computational Intelligence and Neuroscience, 2022, ID 8468438. https://doi.org/10.1155/2022/8468438

Gan, Q. (2022). A logistics distribution route optimization model based on hybrid intelligent algorithm and its application. Annals of Operations Research, 1-13. https://doi.org/10.1007/s10479-022-04854-6

Ma, X., & Wang, F. (2022). Logistic Distribution Route Optimization Based on RFID and Sensor Technology. Wireless Communications and Mobile Computing, 2022, ID 7599539. https://doi.org/10.1155/2022/7599539

Wu, D., Zhu, Z., Hu, D., & Mansour, R. F. (2022). Optimizing Fresh Logistics Distribution Route Based on Improved Ant Colony Algorithm. Computers, Materials & Continua, 73(1), 2079-2095. https://doi.org/10.32604/cmc.2022.027794

Liu, W. (2020). Route optimization for last-mile distribution of rural e-commerce logistics based on ant colony optimization. IEEE Access, 8, 12179-12187. https://doi.org/10.1109/ACCESS.2020.2964328

Stopka, O. (2022). Modelling Distribution Routes in City Logistics by Applying Operations Research Methods. Promet-Traffic&Transportation, 34(5), 739-754. https://doi.org/10.7307/ptt.v34i5.4103

Yu, L. (2021). A route optimization model based on cold chain logistics distribution for fresh agricultural products from a low-carbon perspective. Fresenius Environmental Bulletin, 30(2), 1112-1124.

Yan, L., Grifoll, M., & Zheng, P. (2020). Model and algorithm of two-stage distribution location routing with hard time window for city cold-chain logistics. Applied sciences, 10(7), 2564. https://doi.org/10.3390/app10072564

Liu, B. B. (2021). Logistics distribution route optimization model based on recursive fuzzy neural network algorithm. Computational Intelligence and Neuroscience, 2021, ID 3338840. https://doi.org/10.1155/2021/3338840

Zhao, J., Xiang, H., Li, J., Liu, J., & Guo, L. (2020). Research on logistics distribution route based on multi-objective sorting genetic algorithm. International Journal on Artificial Intelligence Tools, 29(7-8), ID 2040020. https://doi.org/10.1142/S0218213020400205

Li, X. (2022). Multiparty coordinated logistics distribution route optimization based on data analysis and intelligent algorithm. Journal of Sensors, 2022, ID 6053332. https://doi.org/10.1155/2022/6053332

Liu, D., Hu, X. L., & Jiang, Q. (2023). Design and optimization of logistics distribution route based on improved ant colony algorithm. Optik, 273, ID 170405. https://doi.org/10.1016/j.ijleo.2022.170405

Sun, Q., Zhang, H., & Dang, J. (2022). Two-stage vehicle routing optimization for logistics distribution based on HSA-HGBS algorithm. IEEE Access, 10, 99646-99660. https://doi.org/10.1109/ACCESS.2022.3206947

Xiong, H. (2021). Research on cold chain logistics distribution route based on ant colony optimization algorithm. Discrete Dynamics in Nature and Society, 2021, ID 6623563. https://doi.org/10.1155/2021/6623563

Ouyang, F. (2020). Research on port logistics distribution route planning based on artificial fish swarm algorithm. Journal of Coastal Research, Special Issue 115, 78-80. https://doi.org/10.2112/JCR-SI115-023.1

Cui, H. X., Qiu, J. L., Cao, J. D., Guo, M., Chen, X. Y., & Gorbachev, S. (2023). Route optimization in township logistics distribution considering customer satisfaction based on adaptive genetic algorithm. Mathematics and Computers in Simulation, 204, 28-42. https://doi.org/10.1016/j.matcom.2022.05.020

Yu, X. S. (2019). On-line ship route planning of cold-chain logistics distribution based on cloud computing. Journal of Coastal Research, Special Issue 93, 1132-1137. https://doi.org/10.2112/SI93-164.1

Zheng, H. Y., Gao, J., Xiong, J. X., Yao, G. L., Cui, H. J., & Zhang, L. R. (2022). An enhanced artificial electric field algorithm with sine cosine mechanism for logistics distribution vehicle Routing. Applied Sciences-Basel, 12(12), 6240. https://doi.org/10.3390/app12126240

Luo, L. L., & Chen, F. (2022). Multi-objective optimization of logistics distribution route for industry 4.0 using the hybrid genetic algorithm. IETE Journal of Research. https://doi.org/10.1080/03772063.2022.2054869

Cai, L. Y. (2023). Decision-making of transportation vehicle routing based on particle swarm optimization algorithm in logistics distribution management. Cluster Computing-The Journal of Networks Software Tools and Applications, 26(6), 3707-3718. https://doi.org/10.1007/s10586-022-03730-z

Li, S., Zhang, H. H., Li, Z. L., & Liu, H. (2021). An air route network planning model of logistics UAV terminal distribution in urban low altitude airspace. Sustainability, 13(23), 13079. https://doi.org/10.3390/su132313079

Liu, L., Su, B., & Liu, Y. (2021). Distribution route optimization model based on multi-objective for food cold chain logistics from a low-carbon perspective. Fresenius Environmental Bulletin, 30(2), 1538-1549.

Zhao, Z. X., Li, X. M., Zhou, X. C. (2020). Distribution route optimization for electric vehicles in urban cold chain logistics for fresh products under time-varying traffic conditions. Mathematical Problems in Engineering, 2020, ID 9864935. https://doi.org/10.1155/2020/9864935