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Open Access

Vehicle routing optimization algorithm based on time windows and dynamic demand

Jun LI( )Yurong DUANWeiwei ZHANGLiyuan ZHU
School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
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Abstract

To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand, customer cancellation service, and change of customer delivery address, based on the ideas of pre-optimization and real-time optimization, a two-stage planning model of dynamic demand based vehicle routing problem with time windows was established. At the pre-optimization stage, an improved genetic algorithm was used to obtain the pre-optimized distribution route, a large-scale neighborhood search method was integrated into the mutation operation to improve the local optimization performance of the genetic algorithm, and a variety of operators were introduced to expand the search space of neighborhood solutions; At the real-time optimization stage, a periodic optimization strategy was adopted to transform a complex dynamic problem into several static problems, and four neighborhood search operators were used to quickly adjust the route. Two different scale examples were designed for experiments. It is proved that the algorithm can plan the better route, and adjust the distribution route in time under the real-time constraints. Therefore, the proposed algorithm can provide theoretical guidance for suppliers to solve the dynamic demand based vehicle routing problem.

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Journal of Measurement Science and Instrumentation
Pages 369-378
Cite this article:
LI J, DUAN Y, ZHANG W, et al. Vehicle routing optimization algorithm based on time windows and dynamic demand. Journal of Measurement Science and Instrumentation, 2024, 15(3): 369-378. https://doi.org/10.62756/jmsi.1674-8042.2024038

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Received: 19 September 2023
Revised: 06 December 2023
Accepted: 11 December 2023
Published: 30 September 2024
© The Author(s) 2024.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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