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Journal of System Simulation

Abstract

Abstract: Real-time and precise passenger flow simulation provides critical data support for the optimal allocation of resources in public building facilities and the rational design of spatial layouts. This study proposed a self-calibrating passenger flow simulation and spatial optimization method for public buildings based on the GRU-simulated annealing algorithm. A simulation model incorporating spatial structures and flow lines was constructed using Anylogic. A self-calibrating passenger flow simulation method for public buildings was designed based on the GRU-simulated annealing algorithm and applied to the outpatient department of a hospital in Shanghai for passenger flow simulation. The effectiveness of the method was validated by comparing the simulation results with actual data. Spatial layout optimization schemes were proposed to address passenger flow congestion issues observed during the simulation, and the optimization results were visualized. An optimization metric system was developed to assess the effectiveness of the optimization. Practical application demonstrates that this method can effectively identify bottlenecks in the spatial layout of public building facilities. After implementing targeted layout optimization schemes, queuing time is reduced by 24.14%; the service level of the facilities is significantly improved, and passenger density is decreased by 58.93%, thereby mitigating passenger gathering risks and reducing overall infection hazards.

First Page

2826

Last Page

2838

CLC

TP391.9

Recommended Citation

Xu Jinglin, Chen Qianru, Peng Yang, et al. Self-calibrating Passenger Flow Simulation and Spatial Optimization for Public Building Based on GRU-SA[J]. Journal of System Simulation, 2025, 37(11): 2826-2838.

Corresponding Author

Chen Qianru

DOI

10.16182/j.issn1004731x.joss.24-0704

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