Laplacian energy maximizationfor multi-layer air transportation networks  

多层航空网络拉普拉斯能量最大化问题（英文）

作　　者：Zheng Yue Li Wenquan Qiu Feng Cao Xi 

机构地区：[1]School of Transportation, Southeast University, Nanjing 210096, China [2]Department of Computer Science, University of Victoria, Victoria V8W3P6, Canada [3]College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

出　　处：《Journal of Southeast University(English Edition)》2017年第3期341-347,共7页东南大学学报（英文版）

基　　金：The National Natural Science Foundation of China(No.61573098,71401072);the Natural Science Foundation of Jiangsu Province(No.BK20130814)

摘　　要：To increase airspace capacity, alleviate flight delay,and improve network robustness, an optimization method of multi-layer air transportation networks is put forward based on Laplacian energy maximization. The effectiveness of taking Laplacian energy as a measure of network robustness is validated through numerical experiments. The flight routes addition optimization model is proposed with the principle of maximizing Laplacian energy. Three methods including the depth-first search( DFS) algorithm, 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 is 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 the air transportation network on different scales.To increase airspace capacity, alleviate flight delay,and improve network robustness, an optimization method ofmulti-layer air transportation networks is put forward based onLaplacian energy maximization. The effectiveness of takingLaplacian energy as a measure of network robustness isvalidated through numerical experiments. The flight routesaddificm optimization model is proposed with the principle ofmaximizing Laplacian energy. Three methods including thedepth-first search （DFS） algorithm, greedy algorithm andMonte-Carlo tree search （MCTS） algorithm are applied tosolve the proposed problem. The trade-off between systemperformance and computational efficiency is compared throughsimulation experiments. Finally, a case study on Chineseairport network （CAN） is conducted using the proposedmodel. Through encapsulating it into multi-layer infrastructurevia k-core decomposition algorithm, Laplacian energymaximization for the sub-networks is discussed which canprovide a useful tool for the decision-makers to optimize therobustness of the air transoortation network on different scales.

关 键 词：air TRANSPORTATION network LAPLACIAN ENERGY ROBUSTNESS MULTI-LAYER NETWORKS 

分 类 号：N0[自然科学总论—科学技术哲学]