Research On Simulation And Optimization Of Passenger Check-in System At K Airport

Rapid rise as the country’s economic strength,people’s pursuit of quality of life have also been improved,more and more people choose to go out tourism,more fast and comfortable way of aircraft become more and more people choose to travel,this leads to many of the airport terminal traffic is saturated and even exceeded its design construction is expected to traffic.Therefore,the country vigorously carries out the construction of new airports and new terminals,increases the number of flights and expands flight routes,so as to meet the larger civil aviation flow in the future,and at the same time puts forward higher requirements for the development of civil aviation services.How to improve the check-in service efficiency of departing passengers,reduce waiting time and improve passenger service satisfaction has become an important research direction in the development of civil aviation high quality service.Therefore,this paper designs and improves the genetic algorithm,proposes an adaptive genetic algorithm with parallel fusion mechanism,establishes the check-in service system model in the simulation software based on the actual survey data and the idea of digital twin,and uses the improved algorithm to run the simulation model for experiments.The optimal combination of factors and parameters of the check-in service system with the shortest waiting time is obtained.First of all,the check-in service system of the airport terminal is investigated and introduced in detail,and the main problems of the check-in service are analyzed,as well as the factors that affect the service efficiency among the processes,and the methods used to optimize the problems are proposed,which provide the main ideas for the article.Secondly,the check-in system problem can be regarded as an optimal combination problem.By elite reserved strategy and random traversal sampling method,strengthen the individual selection operation of genetic algorithm,the adaptive genetic factor design method,according to the fitness value to determine the genetic operators of different chromosomes,introducing parallel fusion resolution mechanism design a parallel fusion mechanism of the adaptive genetic algorithm,improve the problems of optimum combination optimization ability.The improved algorithm is proved to be better than the traditional genetic algorithm by running the two models in the ideal state of simplified check-in service for ten times.Then,the number factor of the opening of the check-in counter in the influencing factors is studied.Through the investigation of the actual situation of the airport and relevant personnel,the real airport data are obtained,and the obtained data are statistically sorted out.Through the queuing theory and other relevant knowledge,the mathematical model related to the number of check-in counters is designed and the simulation experiment of check-in counters is established.Combined with the problem of system cost,through the simulation experiment on the number of different open service counters,the number of open counters under the minimum cost can be obtained,so as to determine the number range of open check-in counters,as an important parameter in the study of comprehensive factors.Finally,according to the actual operation mode of airport check-in,a digital twin model is established in the simulation tool,and all the factors affecting the efficiency are comprehensively considered: the control mode of virtual window,the speed of conveyor belt,the length of virtual window and the number of open check-in counters.In the case of actual passenger arrival distribution,an adaptive genetic algorithm with parallel fusion mechanism is introduced to optimize the combination of factors and parameters so as to obtain the minimum queuing waiting time.The experimental results show that the optimized check-in efficiency is not only improved,but also may reduce the check-in cost to a certain extent.