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Integrated Arrival and Departure Schedule Optimization Under UncertaintyIn terminal airspace, integrating arrivals and departures with shared waypoints provides the potential of improving operational efficiency by allowing direct routes when possible. Incorporating stochastic evaluation as a post-analysis process of deterministic optimization, and imposing a safety buffer in deterministic optimization, are two ways to learn and alleviate the impact of uncertainty and to avoid unexpected outcomes. This work presents a third and direct way to take uncertainty into consideration during the optimization. The impact of uncertainty was incorporated into cost evaluations when searching for the optimal solutions. The controller intervention count was computed using a heuristic model and served as another stochastic cost besides total delay. Costs under uncertainty were evaluated using Monte Carlo simulations. The Pareto fronts that contain a set of solutions were identified and the trade-off between delays and controller intervention count was shown. Solutions that shared similar delays but had different intervention counts were investigated. The results showed that optimization under uncertainty could identify compromise solutions on Pareto fonts, which is better than deterministic optimization with extra safety buffers. It helps decision-makers reduce controller intervention while achieving low delays.
Document ID
Document Type
Preprint (Draft being sent to journal)
Xue, Min (California Univ. Santa Cruz, CA, United States)
Zelinski, Shannon (NASA Ames Research Center Moffett Field, CA United States)
Date Acquired
June 30, 2014
Publication Date
May 31, 2014
Publication Information
Publication: AIAA Journal of Aircraft
Subject Category
Air Transportation and Safety
Report/Patent Number
Funding Number(s)
WBS: WBS 411931
Distribution Limits
Public Use Permitted.
stochastic optimization
optimization under uncertianty
aircraft shceduling

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