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Research on Optimization Method Based on Complex Network for Crossing Waypoints Location

Author: ChenCaiLong
Tutor: CaoXianBin
School: University of Science and Technology of China
Course: Computer Software and Theory
Keywords: The route convergence point layout problem Complex networks Betweenness Particle swarm optimization Multi-objective optimization
CLC: V249.1
Type: Master's thesis
Year: 2011
Downloads: 166
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Abstract

With the rapid development of the civil aviation industry, the existing route network has been unable to meet the needs of the growing air traffic, it is necessary to carry out a scientific and efficient route network planning. Which route convergence point layout is the core issue of the route network planning, it is aimed at the rational distribution of communication, navigation and surveillance facilities, scientific distribution and use of airspace resources, improve air transportation performance. Solve the route convergence point layout problem starting from the economic interests of the airline, the pursuit of maximum flight efficiency, able to achieve satisfactory results in the case of relatively low air traffic. However, the blind pursuit of maximum flight efficiency may make the route network into congestion; With the rapid development of China's civil aviation industry, and air traffic dramatic growth, arising from the airspace congestion and flight delays have become increasingly prominent. The lack of effective means of disposing of these congestion problems become the major bottleneck of the existing methods, the airspace congestion has become a pressing problem in the route convergence point layout problem. In this paper, the characteristics of the route convergence point layout problem, establish a route network traffic flow model, a based on betweenness guide the single objective particle swarm optimization and the introduction of the multi-objective particle swarm algorithm airspace capacity. The completed work including: (1) the existing the route convergence point layout method based on flight efficiency maximum flight efficiency, may lead to the route network into congestion. To solve the problem, the paper first route network traffic flow modeling analysis to obtain the heuristic knowledge of the layout of the the guidance route aggregation point; then in the traditional single objective particle swarm algorithm framework, airspace congestion as one of the constraints, the consolidated The congestion Rules, a based on betweenness guide the heuristic particle swarm algorithm to solve the the route convergence point layout, to maximize flight efficiency in the pursuit of the case to ensure that the route network congestion. (2) the current flight efficiency as the only optimization objective the route convergence point layout method ignores an important route network traffic performance indicators - airspace capacity, optimized route network with increasing air traffic congestion will soon fall into . Solve the problem, this paper proposes a way to introduce the airspace capacity multi-objective particle swarm optimization method, while optimizing flight efficiency and airspace capacity. First, through a complex network modeling gives a quantitative description of the method of airspace capacity; then build a standard deviation of total airline spend and referral number multi-objective optimization model; Finally, the the route convergence point layout problem using multi-objective particle swarm algorithm non-dominated solution set. The method of taking into account the flight efficiency and airspace capacity, the face of the growth in air traffic of the route network can effectively delay the emergence of airspace congestion.

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