Models And Algorithms Of Bilateral Negotiation Game And Optimal Allocation For International Air Traffic Rights

Air Traffic Rights(ATR)are indispensable key elements for airlines for their international air transport business.However,ATR often need to be determined through bilateral or multilateral negotiations between countries.There are usually restrictions on ATR between China and developed countries in Europe and the United States,involving designated airlines numbers,route schedules,transport capacity entitlements and so on.Airlines cannot obtain unlimited ATR resources required for their own development.ATR resources,especially scarce ones,have become one of the main bottlenecks restricting the development of China’s large airlines and international hub airports,which urgently requires the Civil Aviation Administration of China(CAAC)to strive for more high-value ATR resources through negotiation,and allocate the obtained ATR resources to airlines and airports reasonably.Therefore,aiming at the two core phases of the ATR bilateral negotiation and the ATR resource allocation,the general goal of this dissertation studies the sequential reciprocal game problem for the ATR negotiation and the Air Traffic Rights Allocation Problem(ATRAP)respectively,so as to provide scientific theories and methods for government regulators in the decision-making process on the ATR negotiation and the ATR resource allocation.The main work of this dissertation is as follows:(1)Identification of ATR negotiation and the ATR allocation problem is as follows.First,this dissertation systematically analyzes and summarizes the concept and development process of ATR,the evolution process of ATR negotiation modes,the types of ATR agreements and the negotiation process in China,and the allocation methods of ATR resources in developed countries and China.Then,we analyze and identify the problems in the theory and application of the ATR negotiation and resource allocation.The game problem of the ATR negotiation,and the ATR allocation problem are proposed.(2)The sequential reciprocal game of bilateral negotiations on air traffic rights is studied.In the bilateral negotiations,it is necessary to set up topics of air traffic rights(TATR)in order to reach the expanding commercial cooperation arrangements of air rights.This dissertation divides TATR into short-term topics and long-term topics according to the demand urgency of TATR and also divides TATR into base topics and extension topics according to the degree of cooperation.And the material income and the reciprocal psychological income are introduced to measure the value of TATR.Material income functions are proposed to evaluate short-term topics and long-term topics respectively,taking into account the bargaining power,the compensation for related industries,the value of reserved space and the lost value by resource vacancy.On this basis,six game scenarios are summarized based on the characteristics of the material income of the extension topics,and the material income matrix is established based on the game strategy set(maximum cooperation and minimum cooperation).Then,the comprehensive income function is established by considering the material income and the reciprocal psychological income under different reciprocal motives.In the game strategy selection,not only the comprehensive benefits,but also the game behavior of the negotiating opponent should be considered.Therefore,we set up a sequential reciprocal game model,which can be applied to different game scenarios.We analyze the sequential reciprocal equilibrium conditions under the different game strategies,and obtain the conditions to be satisfied by core indicators such as reciprocity sensitivity coefficient.Finally,numerical simulation experiments are carried out to simulate the game between the two countries with reciprocal relationship.The results show that the reciprocity sensitivity coefficient,the topics of air traffic rights scales,the opportunity cost vacancy loss coefficient and the value of reserved space in industrial space determine the game strategy of the negotiators jointly when the two countries have the reciprocal relationship.Finally,the numerical simulation results are compared with the traffic rights negotiation of China-Britain and China-France,in order to verify the effectiveness of the sequential reciprocal game model of traffic rights negotiation in this paper.(3)The competitiveness evaluation of airlines for the ATR resource allocation is conducted.The competitiveness of airlines is an important factor affecting the optimal allocation of ATR resources.According to the ATR resource allocation requirements,the factors affecting the competitiveness of airlines are analyzed from three aspects including safety,service,and sustainable operation ability.An evaluation index system of the competitiveness of airlines is established.Then,this dissertation uses self-organizing feature mapping neural network(SOM)and grey system theory to evaluate the competitiveness of airlines respectively.The SOM method is used to carry out self-organizing learning on the sample set without supervision and prior knowledge.Then,the grey system theory is used to score the actual monitoring data of each airline and the competitiveness of airlines is analyzed by grey cluster analysis to determine the evaluation level of airline competitiveness.Finally,a cross validation is carried out.When the evaluation grade results of the two methods are consistent,the competitiveness evaluation value of each airline is obtained,so as to provide parameters for the optimal allocation model of ATR resources.(4)The optimization model and algorithm of ATR resource allocation is proposed.After the ATR agreements are signed,the government authorities need to allocate the ATR resources according to the passenger demands and the development requirements of the civil aviation industry reasonably.Based on the known OD demand of passengers,the Air Traffic Rights Allocation Problem(ATRAP)for multiple ATR agreements is proposed,and a multi-objective mixed integer programming model is developed.The model considers passengers’ travel mileage,the position of international hub airport,the competitiveness level and market share of airlines,and allocates scarce ATR resources to airlines and airports reasonably.A hybrid approach(HGA-VNS)combining Variable Neighborhood Search(VNS)and Genetic Algorithm(GA)is developed.The approach takes GA as the main framework,and after each iteration of GA,the variable neighborhood descent algorithm(VSD)is adopted to further optimize the best solution so far,so as to strengthen the search ability of GA.According to the actual data of the industry,the numerical example is designed,and solved by CPLEX,GA and HGA-VNS respectively.The sensitivity of key parameters in the model is analyzed.The experimental results show that the ATR resource allocation result is reasonable,and HGA-VNS has high search efficiency and can solve the ATRAP effectively.(5)The analysis and application of optimal allocation of ATR resources is conducted.With the actual data of China’s civil aviation,the model and algorithm are applied to allocation of ATR resources of Sino-France and Sino-many countries(Britain and France).The results are compared with the actual allocation schemes to further verify the effectiveness of the model and algorithm.On this basis,the proposed model is applied to Sino-France ATR bilateral negotiations to determine the benefits brought by the increase of ATR resources,so as to provide a basis for raising the issue of high-quality ATR increment in the future ATR negotiations.Moreover,the proposed model is also applied to Beijing Daxing International Airport to obtain more ATR resources and build an international route network,so as to realize the direction of Beijing’s “one city,two airports” international double hub.