A Mathematical Programming Approach to Optimum Airspace Sectorisation Problem

[1]  Daniel Delahaye,et al.  Dynamic airspace configuration by genetic algorithm , 2017 .

[2]  M Germanus Alex,et al.  A Comparative Study to Evaluate the Performance of Classification Algorithms in Mammogram Analysis , 2018 .

[3]  Yangzhou Chen,et al.  Dynamic airspace configuration method based on a weighted graph model , 2014 .

[4]  Alexandre M. Bayen,et al.  A Weighted-Graph Approach for Dynamic Airspace Configuration , 2007 .

[5]  Dapeng Wu,et al.  A knowledge-transfer-based learning framework for airspace operation complexity evaluation , 2018, Transportation Research Part C: Emerging Technologies.

[6]  Joseph S. B. Mitchell,et al.  Geometric algorithms for optimal airspace design and air traffic controller workload balancing , 2008, JEAL.

[7]  W. Ochieng,et al.  Estimation of European Airspace Capacity from a Model of Controller Workload , 2002, Journal of Navigation.

[8]  Marc Schoenauer,et al.  Airspace sectoring by evolutionary computation , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[9]  Arash Yousefi,et al.  Optimum airspace design with air traffic controller workload-based partitioning , 2005 .

[10]  Hartmut Fricke,et al.  Air traffic control complexity as workload driver , 2010 .

[11]  Yanjun Wang,et al.  Empirical analysis of air traffic controller dynamics , 2013 .

[12]  Arnab Majumdar,et al.  A method to estimate air traffic controller mental workload based on traffic clearances , 2014 .

[13]  Michael Schultz,et al.  Dynamic airspace sectorisation for flight-centric operations , 2018, Transportation Research Part C: Emerging Technologies.

[14]  Xianbin Cao,et al.  Measuring air traffic complexity based on small samples , 2017 .

[15]  Hakan Oktal,et al.  A new approach to air traffic controller workload measurement and modelling , 2011 .