Preference-based 3-dimensional en-route airspace sectorization
Author:
Affiliation:
1. Nanyang Technological University, Singapore
Funder
Civil Aviation Authority of Singapore
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3205455.3205565
Reference22 articles.
1. Federal Aviation Administration. 2017. FAA Aerospace Forecast Fiscal Years 2017--2037. https://www.faa.gov/data_research/aviation/aerospace_forecasts/media/FY2017-37_FAA_Aerospace_Forecast.pdf. (2017). Federal Aviation Administration. 2017. FAA Aerospace Forecast Fiscal Years 2017--2037. https://www.faa.gov/data_research/aviation/aerospace_forecasts/media/FY2017-37_FAA_Aerospace_Forecast.pdf. (2017).
2. A comprehensive preference-based optimization framework with application to high-lift aerodynamic design
3. A fast and elitist multiobjective genetic algorithm: NSGA-II
4. Reference Point Based Multi-Objective Optimization Using Evolutionary Algorithms
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