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Preface; Contents; Committee Members' List; EIWAC2015 Technical Program Committee; Editor in Chief; Editors; Associate Editor; Secretaries; Part I Introduction; Introduction to the Fourth ENRI International Workshop on ATM/CNS (EIWAC 2015); 1 Introduction; 2 Overview of EIWACs; 3 Keynote Speeches; 3.1 Hitoshi Ishizaki, "Toward the Realization of Seamless SKY in the Asia Pacific Region"; 3.2 Richard Macfarlane, "ICAO's Global Air Navigation Plan and the Importance of Being Earnest about the ASBUs"
3.3 Michael Standar, "SESAR
The European Approach to Support Global Harmonization and Interoperability"3.4 Philippe Merlo, "CNS in ATM: The Challenges Ahead"; 3.5 Neil Planzer/Chris Metts, "how Do they all Cometogether … SESAR, NextGen and ASBU"; 3.6 Blair Cowles, "The Operators' Perspective on ATM Modernization"; 3.7 Christian Schleifer-Heingärtner, "Standards to Ensure Global Harmonization and Worldwide Interoperability"; 3.8 Edward Bolton, "The NextGen Role in Global Research and Development Coordination"
3.9 Akbar Sultan, "Collaborative R&D for NextGen and Global Harmonization to Inform ASBUs Blocks 2 and 3"3.10 Kazuo Yamamoto, "ENRI's R&D Activities for Globally Harmonized ATM Environment"; 4 Invited Talks for Global Harmonization; 4.1 Patrick SOUCHU, "Moving from SESAR R&D Activities to Implementation: An ANSP Perspective"; 4.2 Mohamed Faisal Bin Mohamed SALLEH, "ATM Research and Development for Asia Pacific"; 4.3 Yasuhiro Koshioka, "DREAMS Project, Its Results, and Implementation Status"; 5 Conclusions; References; Part II Trajectory Planning and Optimization
Large-Scale 4D Trajectory Planning1 Introduction; 2 Previous Related Works; 3 Mathematical Modeling; 3.1 Uncertainties; 3.1.1 Deterministic Model; 3.1.2 Probabilistic Model; 3.2 Interaction Between Trajectories; 3.3 Route/Departure Time/Flight Level Allocation; 4 Interaction Detection; 5 Resolution Algorithm; 5.1 Simulated Annealing; 5.2 Hill-Climbing Local Search; 5.3 Hybrid Algorithm; 6 Numerical Results; 6.1 Deterministic Uncertainty Model; 6.2 Probabilistic Uncertainty Model; 7 Conclusions; References; Aircraft Trajectory Planning by Artificial Evolution and Convex Hull Generations
1 Introduction2 State of the Art; 3 Optimization Model and Algorithm; 3.1 Trajectory Shape Design; 3.2 Decision Variables; 3.3 Objective Function; 3.4 Genetic Algorithm; 4 Model Extension; 4.1 Adding a Time Dimension; 4.1.1 New Obstacle's Definition; 4.1.2 Obstacles Intersection; 4.2 Solution Approach; 4.2.1 First Approach; 4.2.2 Cluster Approach; 4.2.3 Genetic Algorithm: New Chromosome Definition; 5 Some Results with Moving Obstacles; 6 Conclusion; References; Homotopy Route Generation Model for Robust Trajectory Planning; 1 Introduction; 2 Previous Research; 3 Robust Trajectory Planning
3.3 Michael Standar, "SESAR
The European Approach to Support Global Harmonization and Interoperability"3.4 Philippe Merlo, "CNS in ATM: The Challenges Ahead"; 3.5 Neil Planzer/Chris Metts, "how Do they all Cometogether … SESAR, NextGen and ASBU"; 3.6 Blair Cowles, "The Operators' Perspective on ATM Modernization"; 3.7 Christian Schleifer-Heingärtner, "Standards to Ensure Global Harmonization and Worldwide Interoperability"; 3.8 Edward Bolton, "The NextGen Role in Global Research and Development Coordination"
3.9 Akbar Sultan, "Collaborative R&D for NextGen and Global Harmonization to Inform ASBUs Blocks 2 and 3"3.10 Kazuo Yamamoto, "ENRI's R&D Activities for Globally Harmonized ATM Environment"; 4 Invited Talks for Global Harmonization; 4.1 Patrick SOUCHU, "Moving from SESAR R&D Activities to Implementation: An ANSP Perspective"; 4.2 Mohamed Faisal Bin Mohamed SALLEH, "ATM Research and Development for Asia Pacific"; 4.3 Yasuhiro Koshioka, "DREAMS Project, Its Results, and Implementation Status"; 5 Conclusions; References; Part II Trajectory Planning and Optimization
Large-Scale 4D Trajectory Planning1 Introduction; 2 Previous Related Works; 3 Mathematical Modeling; 3.1 Uncertainties; 3.1.1 Deterministic Model; 3.1.2 Probabilistic Model; 3.2 Interaction Between Trajectories; 3.3 Route/Departure Time/Flight Level Allocation; 4 Interaction Detection; 5 Resolution Algorithm; 5.1 Simulated Annealing; 5.2 Hill-Climbing Local Search; 5.3 Hybrid Algorithm; 6 Numerical Results; 6.1 Deterministic Uncertainty Model; 6.2 Probabilistic Uncertainty Model; 7 Conclusions; References; Aircraft Trajectory Planning by Artificial Evolution and Convex Hull Generations
1 Introduction2 State of the Art; 3 Optimization Model and Algorithm; 3.1 Trajectory Shape Design; 3.2 Decision Variables; 3.3 Objective Function; 3.4 Genetic Algorithm; 4 Model Extension; 4.1 Adding a Time Dimension; 4.1.1 New Obstacle's Definition; 4.1.2 Obstacles Intersection; 4.2 Solution Approach; 4.2.1 First Approach; 4.2.2 Cluster Approach; 4.2.3 Genetic Algorithm: New Chromosome Definition; 5 Some Results with Moving Obstacles; 6 Conclusion; References; Homotopy Route Generation Model for Robust Trajectory Planning; 1 Introduction; 2 Previous Research; 3 Robust Trajectory Planning