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.
Recommended Citation
Ma, Huawei and Yan, Boying
(2025)
"Vehicle Routing Problem with Drones Considering Zoned Distribution of Epidemic Prevention Materials,"
Journal of System Simulation: Vol. 37:
Iss.
1, Article 19.
DOI: 10.16182/j.issn1004731x.joss.23-1022
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol37/iss1/19
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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