Abstract
In this paper, the author set up an index system on the airport collaboration of the multi-airport system (MAS), including the number of external routes, the total cost of the route network, the passenger volume of the MAS, the airport primacy ratio, the route repetition rate, the capacity utilization and the purpose matching rate of airport. Next, the airports within the same MAS are regarded as one airport in the general sense, and the ground transit between the internal airports and the external routes from the single airport are combined to satisfy the demand for passenger transport in the MAS. On this basis, a mathematical model was constructed for collaborative optimization of the route network of the MAS, and used to determine the transit airport and its passenger volume. The indices were transformed into constraints and optimization objectives. Taking the MAS in the Beijing-Tianjin-Hebei (BTH) region for example, the model settings and parameters were further refined. Through model simulation, the collaborative optimization model was further improved, allowing two internal airports to serve as transit airports. The empirical results show that the collaborative optimization successfully improved the overall efficiency of the MAS, clarified the division of labor among the internal airports and balanced the allocation of aviation resources.
Highlights
With the development of regional economy and integrated transport, many airports in the same region have increasingly deep interactions, forming a multi-airport system (MAS)
One of the three largest internal airports was selected as the transit airport, and the passengers in the other internal airports were relocated to the transit airport via ground transport, thereby reducing the total cost of the route network, enhancing the purpose matching rate of the transit airport, and lowering the route repetition rate
Formula (2) limits the number of external routes in the MAS, that is, the external routes can only start from one internal airport at the most; formula (3) requires that the passenger volume after the transit should not surpass the design capacity of the airport; formula (4) means the passengers originally in route (i, j) are all transferred to the transit airport; formula (5) specifies that the passenger volume on any external route after the transit should not exceed the capacity of that route
Summary
With the development of regional economy and integrated transport, many airports in the same region have increasingly deep interactions, forming a multi-airport system (MAS). L. Zhang et al.: Collaborative Route Optimization Model for Regional MAS the choice of airline network structure type under the mode of amalgamation of enterprise or oligopoly. Du et al [17] and Wei [18] used complex network theory to analyze the importance of nodes and routes in airline network. Jiang et al [21] coordinated and optimized the traffic and capacity of the route network for multiple airports. Derudder et al [22] investigated the impacts of different route networks on the airport functions in New York MAS and the other three MASs in the US. The relevant collaborative optimization studies mainly tackle the economic development of the MAS, failing to consider the overall planning of the route network for the MAS. The research findings promote the synergic development of the airports in the MAS, giving full play to the advantages of each airport
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