Optimization of Urban Agglomeration Transportation Network Evacuation Paths

doi:10.16182/j.issn1004731x.joss.23-1242

Abstract

Abstract:

Given the complexity of the internal transportation network structure within urban agglomerations and the presence of numerous alternative routes, this paper proposes an enhanced ant colony algorithm to address the evacuation path problem of urban agglomeration transportation networks. A comprehensive urban agglomeration transportation network model is constructed, in which the issue of virtual transfer edges within the urban scope is considered and a weighting function is constructed taking into account the travelling time cost and the transferring time cost. Optimizations are applied to the ant colony algorithm, constructing an adaptive adjustment of state transitions and an information pheromone update rule aiming at accelerating convergence speed. The results show that the improved ant colony algorithm can effectively improve the convergence efficiency, reduce the number of evacuation path nodes, and decrease the total evacuation cost, demonstrating strong robustness.

Key words: urban agglomeration, network model, emergency evacuation, ant colony algorithm, path optimization

CLC Number:

U491

He Bowei, Li Chengbing, Nie Shida, Wang Jialin. Optimization of Urban Agglomeration Transportation Network Evacuation Paths[J]. Journal of System Simulation, 2024, 36(12): 2937-2944.

Figures/Tables 6

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算法	最优路径	最优疏散成本/min
Dijkstra	13-14-39-6-3-34-33-59	372.83
GA	13-5-40-6-7-32-59	379.61
ACO	13-11-12-10-15-7-3-34-33-59	366.02
IACO	13-11-12-1-32-59	282.81

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