Journal of System Simulation
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.
Recommended Citation
He, Bowei; Li, Chengbing; Nie, Shida; and Wang, Jialin
(2024)
"Optimization of Urban Agglomeration Transportation Network Evacuation Paths,"
Journal of System Simulation: Vol. 36:
Iss.
12, Article 16.
DOI: 10.16182/j.issn1004731x.joss.23-1242
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol36/iss12/16
First Page
2937
Last Page
2944
CLC
U491; TP391
Recommended Citation
He Bowei, Li Chengbing, Nie Shida, et al. Optimization of Urban Agglomeration Transportation Network Evacuation Paths[J]. Journal of System Simulation, 2024, 36(12): 2937-2944.
DOI
10.16182/j.issn1004731x.joss.23-1242
Included in
Artificial Intelligence and Robotics Commons, Computer Engineering Commons, Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Science Commons