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Journal of System Simulation

Abstract

Abstract: To address the shortcomings of current contactless delivery methods in the collaborative distribution of epidemic prevention supplies, we introduce a specialized model called the vehicle routing problem with drones considering zoned distribution (VRPD-ZD). In order to solve the problem, a linear programming model is established with the shortest delivery time as the optimization objective, and a two-stage heuristic algorithm is proposed. The initial solution is generated by greedy algorithm in the first stage. In the second stage, we develop a Tabu search algorithm with genetic algorithm (TSGA) hybrid. This enhanced algorithm integrates a taboo list and employs advanced chromosome encoding techniques to improve performance. The experimental results show that TSGA compares favourably with the adaptive algorithm based on genetic method (AAGM) as well as the simulated-annealing-based twophase optimization (SATO) in terms of solution quality and solution time. This two-stage algorithm can effectively solve the VRPD-ZD problem and can improve the efficiency of cooperative vehicle-machine distribution of epidemic prevention materials.

First Page

234

Last Page

244

CLC

U116; TP18

Recommended Citation

Ma Huawei, Yan Boying. Vehicle Routing Problem with Drones Considering Zoned Distribution of Epidemic Prevention Materials[J]. Journal of System Simulation, 2025, 37(1): 234-244.

DOI

10.16182/j.issn1004731x.joss.23-1022

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