Queuing Strategy Optimization with Restricted Service Resources

Under the circumstance of congestion, the low-efficiency operation of security system is one of the major causes of frequent security incidents over the span of recent years. At the same time, identifying the potential bottleneck which disrupts the audience is an effective way to explore new solutions of security issues, and use mathematical models to develop the most efficient and effective security screening system. In this paper, the security system of Luzhniki stadium in 2018 is instance model. The queuing theory is used to construct the model (MMS), while according to the Poisson distribution and network science to analyze bottlenecks, models and results. Both practical and cultural factors are considered in the model optimization process. In this way, the target loop checkpoint system is designed, and the convolution neural network algorithm is added to the system to classify and dispose the captured images. The purpose is to improve security efficiency by increasing the flow of people in best use of space.