Title: Optimisation of freight vehicle routes leveraging cloud computing and edge endpoints

Authors: Hongxia Jin

Addresses: Department of Computer Technology, Henan Quality Institute, Pingdingshan, Henan, China

Abstract: In the current freight industry, how to improve the economic benefits of freight transportation and solve the problem of insufficient information timeliness under cloud computing is a persistent challenge. In response to the problems of delayed information in cloud computing path planning and insufficient economic benefits of planning results, this study proposes a freight vehicle path optimisation model supported by cloud computing and edge end. This model introduces edge computing into cloud platforms and constructs a genetic algorithm-based truck path optimisation algorithm. According to test outcomes, the path planning time of the proposed model was at most 160 ms lower than that of a regular cloud computing environment. In simulation testing, the optimised path planning model saved a total cost of 16.8% compared to the pre optimised output. The proposed model effectively optimises the economic benefits of freight transportation and solves the problem of insufficient information timeliness.

Keywords: cloud computing; edge end; path optimisation; iteration; logistics.

DOI: 10.1504/IJVICS.2026.150583

International Journal of Vehicle Information and Communication Systems, 2026 Vol.11 No.1, pp.36 - 52

Received: 24 May 2024
Accepted: 05 Dec 2024
Published online: 17 Dec 2025 *

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