Application Of Multi-objective Optimization In Gate Assignment

In recent years,with the rapid increase in global traffic,the demand for air transport has also shown an upward trend.Airports are increasingly facing capacity pressure,and the complexity of airport management has increased significantly.If they are not properly allocated,flight delays or accidents may occur,and even the domino effect may affect the overall operation of the airport.How to scientifically and rationally allocate airport resources is the premise and guarantee for safe and efficient airport operations.In this paper,firstly,genetic algorithm and tabu search are fused together,and a new and improved genetic algorithm is proposed.Then,with the addition of satellite halls,the issue of transfer passengers’ boarding gate allocation is considered,and a minimum operating cost is established.,The optimization model with the highest customer satisfaction,and then use the improved genetic algorithm to solve the model.The results show that the model optimizes the airport boarding gate allocation,reducing operating costs and improving customer satisfaction.The first chapter mainly gives some research overview of the boarding gate allocation problem,model solving method and genetic algorithm,and puts forward the main research content of this article.The second chapter mainly describes the problem of boarding gate scheduling,including the introduction of civil aviation airports and the allocation of transit passenger boarding gates.It further elaborated the boarding gate allocation process,optimization goals and constraints,and constructed a theoretical basis for this article.The third chapter first introduces the principle of genetic algorithm.In order to prevent the algorithm from premature and get a local optimal solution,the algorithm is improved.Tabu search is used to replace the mutation operation in the standard genetic algorithm,and tabu search is used to replace the mutation operator.And conduct a taboo search for each individual.This algorithm combines tabu search algorithm with genetic algorithm,so as to further strengthen the local search ability under the premise of ensuring the global search ability of the algorithm.Chapter 4 considers customer satisfaction on the basis of a simple flight-gate optimization allocation problem.Taking into account that the establishment of the satellite hall is to ease the pressure on the airport capacity,so that passengers can get better services,but the newly added satellite hall has a certain impact on transit passengers.Therefore,in order to ensure the successful transfer of transit passengers,combining the characteristics of flights and boarding gates,quantitatively analyze various influencing factors,so as to establish a mathematical model of flight-gateway allocation with the smallest terminal operating cost and the highest customer satisfaction.Chapter 5 uses the improved genetic algorithm programming to solve the abovementioned boarding gate allocation optimization model,which is realized with the help of Matlab software.Through the analysis of the allocation results,the validity of the flight-gate optimization allocation model and the algorithm used in this paper is further verified,to a certain extent,it also provides a more comprehensive and reliable solution for airport decision-making.