Research On Time-Slot Resource Optimization Of Sector Based On Dynamic Capacity

With the rapid development of the national economy and the increasing demand for flights,the aviation industry has great potential and prospects for future development.In the face of limited airspace resources and weather-related changes in airspace capacity over time,how to optimise sector time slot resources on the basis of dynamic capacity using scientific and reasonable methods,and to consider the fair allocation of time slot resources to individual airlines,so as to improve the utilisation of airspace resources,reduce flight delays and This will improve the utilisation of airspace resources,reduce flight delays and airspace congestion,and improve the fairness between airlines,which is one of the problems that need to be solved in traffic management.This thesis first gives an overview of the current status of research on dynamic capacity and time slot resource allocation at home and abroad,describes the concepts,methodological divisions and measures of air traffic flow management,summarises the definition of dynamic capacity,impact indicators and common assessment methods,and outlines the theory of time slot allocation and important attributes and other related concepts.Next,based on the analysis of the impact of weather on flight operations and the classification of weather classes,a grid method was used to select a certain size of grid to delineate the weather map covered around the flight segment,and the blocking model established to find the availability of each flight segment,the actual configuration of the sector was considered,and the available capacity ratio of each configuration of the flight segment was separately found out,based on which the final dynamic capacity of the sector was obtained.The final sector dynamic capacity is then obtained based on the dynamic capacity,allocation uniqueness and flight safety interval as important constraints,and the Gini coefficient is added to establish a sector time slot resource optimisation model with minimum flight adjustment cost and minimum fair deviation for each airline.Finally,the NSGA-Ⅱ(Non-dominated Sorting Genetic Algorithm-II)algorithm is designed for the time slot allocation model and the improved NSGA-Ⅱ algorithm is used as a comparative solution algorithm.The simulation results show that with limited airspace resources,the NSGA-Ⅱ algorithm and the improved NSGA-Ⅱ algorithm can adjust the time slots for flights to enter the sector to meet the capacity limit,while taking into account the interests of airlines,and the solution set obtained using the improved NSGA-Ⅱ algorithm is better than the NSGA-Ⅱ algorithm,further This further validates the effectiveness of the improved NSGA-Ⅱ algorithm in solving the multi-objective time slot allocation problem.