01622482

Component

Air transportation network optimization through adding one or more flight routes to the existing network is an effective way to increase airspace capacity, alleviate flight delay, and improve network robustness. In this paper, the authors introduce the flight routes addition problem through maximizing the Laplacian energy which is a fair and promising metric for measuring network robustness. Three methods including depth-first search (DFS), greedy algorithm and Monte-Carlo Tree Search (MCTS) algorithm are applied to solve the proposed problem. The trade-off between system performance and computational efficiency are compared through simulation experiments. Finally, a case study on Chinese airport network (CAN) is conducted using the proposed model. Through encapsulating it into multi-layer infrastructure via k-core decomposition algorithm, Laplacian energy maximization for the sub-networks is discussed which can provide a useful tool for the decision-makers to optimize the robustness of air transportation network in different scales.

This paper was sponsored by TRB committee AV060 Standing Committee on Airfield and Airspace Capacity and Delay.

01618707

17-02361

English

17p

2017

Transportation Research Board 96th Annual Meeting

Digital/other

Figures; References; Tables

Air routes; Air transportation; Airports; Algorithms; Case studies; Networks; Optimization; Simulation

China

Aviation; Planning and Forecasting

Transportation Research Board Annual Meeting 2017 Paper #17-02361

TRIS, TRB, ATRI

Dec 8 2016 10:52AM