Study On Hub Airport Gates Assignment And Capacity Evaluation Based On Cellular Automata

From 1990's of last century, civil aviation transportaion of China has entered into growth phase. For the years of 'the eleventh five year plan' and the 20 years after, the civil aviation of China will maintain a high growth rate and realize the change from a large civil aviation state to a great one. Under this circumstance, there are shortage transport resources in airports, especially hub airports, among which, the shortage of airport gates becoming even more obvious in recent years. The shortage of the airport's gates, not only affects the order and the efficiency of the operation on airport apron, but also limits the flight schedule at the airport, and restricts the airport's rapid development. Under the above situation, with the aim of enhancing airport operation order, with the consideration of transport efficiency in mind, the paper researches on airport gates assignment problem (GAP) and on the assessment of the practical capacity of airport gates under certain operation order.On the basis of GAP, the paper researches on the way to allocate flights to airport gates in hub airports according to different requirement (includes 4 objectives, anti-delay features, high service quality, high operation efficiency and low fuel expense while taxiing); and then, take the solution of GAP as primary condition, via cellular automata simulation of gate operation, researches on under different allocation condition, the appearance and disappearance law of delay due to airport gate occupation conflict (defined as aftereffect delay time, ADT), and establish the functional relation between ADT and buffer time, to do research on theoretical theory of airport gate capacity evaluating calculation.Major innovation of this paper reflected in the following aspects:i. First, based on process of appearance and disappearance of ADT, the paper establishes gate occupation conflict probability theory. Second, based on the theory, the paper studies the establishment of optimized anti-delay hub airport gates assignment model. The paper also resolves GAP based on Genetic Algorithms, and validates the GAP solution with an practical example, which enables the gate assignment plan with better anti-delay and anti-interference capability;ii. The Paper establishes mixed integer programming aiming at minimizing the passenger walk distance and the aircraft taxiing distance, and does optimizing computation for this model through tabu search technique. The practical example validated the feasibility of the model and the algorithms. The optimized gate assignment plan may reduce the total aircraft taxiing distance by 31%, the passenger transit walking distance by 13%, not only reducing the flight taxiing time efficiently but also reducing the walking distance of the passenger in the terminal.iii. The paper Establishes GAP model based on fuel consumption while aircraft is taxiing and GAP model based on gate operation efficiency. The first optimization formulation may reduce aircraft's taxiing distance and time efficiently, raise airlines' economic benefit. While the latter one is established according to gate operation space efficiency and gate operation time efficiency. The paper does optimizing computation on the model with improved tabu search technique, and validated the feasibility of the model and the computation with practical example. Results calculated based on the first model show that, the airport may save 1.71 million yuan on aircraft taxiing fuel consumption, 624 billion annually. With the latter model, the solution will also raise the gate usage efficiency by 20%.iv. Establishment of multi-goals GAP model, taking an integrated consideration of 4 factors, includes aircraft taxiing cost, gate operation efficiency, service quality provided to the passengers and gate occupation conflict probability. To find the solution of the model, the paper presents two computation methods including information entropy measures, as well as fixed weight method respectively.v. Establishment cellular automata (CA) simulation model of apron gates occupation includes CA with non-operation delay under fixed boundary and circular boundary and CA with operational delay under fixed boundary and circular boundary. Secondly, via evolution of the circular boundary CA model, the paper makes analysis on effect of different GAP model made to ADT. Thirdly, the paper researches on the effect of the setting of different buffer time in gate operation time to get the functional relation between buffer time and ADT. Fourthly, applying functional relation between ADT and buffer time based on cellular automata simulation data, to analyze and resolve the problem encountered on setting of necessary buffer time required in gate assignment plan. Finally the paper formulates an optimization model to compute the apron gate capacity considering ADT, fluctuations in flights number and other factors. A real example is presented to justify the validity of the model.In conclusion, the paper researches GAP of different features, including objectives with the consideration of anti-delay features based on conflict probability, services provided to the passengers, gates operation efficiency and aircraft taxiing fuel consumption, meanwhile, the paper establishes optimized multi-goals GAP model which integrated multi-features, having set a foundation for the realization of an automatic and computerized gate allocation. At the same time, the paper, for the first time, set the cellular automata theory as the basis, researches on the appearance and disappearance law of ADT, based on it, taking integrated consideration that limiting ADT, the paper does research on practical airport gate capacity computation theory. The results not only promote requirement for the improvement of the gate operation order but also provide accordance to improving the gate capacity.