Two-stage combinatorial optimization framework for air traffic flow management under constrained capacity

Kim, Bosung

Title:

Two-stage combinatorial optimization framework for air traffic flow management under constrained capacity

dc.contributor.advisor	Clarke, John-Paul B.
dc.contributor.author	Kim, Bosung
dc.contributor.committeeMember	Feron, Eric
dc.contributor.committeeMember	Theodorou, Evangelos
dc.contributor.committeeMember	Egerstedt, Magnus
dc.contributor.committeeMember	Erera, Alan
dc.contributor.department	Aerospace Engineering
dc.date.accessioned	2015-06-08T18:20:39Z
dc.date.available	2015-06-08T18:20:39Z
dc.date.created	2015-05
dc.date.issued	2015-01-09
dc.date.submitted	May 2015
dc.date.updated	2015-06-08T18:20:39Z
dc.description.abstract	Air traffic flow management is a critical component of air transport operations because at some point in time, often very frequently, one of more of the critical resources in the air transportation network has significantly reduced capacity, resulting in congestion and delay for airlines and other entities and individuals who use the network. Typically, these “bottlenecks” are noticed at a given airport or terminal area, but they also occur in en route airspace. The two-stage combinatorial optimization framework for air traffic flow management under constrained capacity that is presented in this thesis, represents a important step towards the full consideration of the combinatorial nature of air traffic flow management decision that is often ignored or dealt with via priority-based schemes. It also illustrates the similarities between two traffic flow management problems that heretofore were considered to be quite distinct. The runway systems at major airports are highly constrained resources. From the perspective of arrivals, unnecessary delays and emissions may occur during peak periods when one or more runways at an airport are in great demand while other runways at the same airport are operating under their capacity. The primary cause of this imbalance in runway utilization is that the traffic flow into and out of the terminal areas is asymmetric (as a result of airline scheduling practices), and arrivals are typically assigned to the runway nearest the fix through which they enter the terminal areas. From the perspective of departures, delays and emissions occur because arrivals take precedence over departures with regard to the utilization of runways (despite the absence of binding safety constraints), and because arrival trajectories often include level segments that ensure “procedural separation” from arriving traffic while planes are not allowed to climb unrestricted along the most direct path to their destination. Similar to the runway systems, the terminal radar approach control facilities (TRACON) boundary fixes are also constrained resources of the terminal airspace. Because some arrival traffic from different airports merges at an arrival fix, a queue for the terminal areas generally starts to form at the arrival fix, which are caused by delays due to heavy arriving traffic streams. The arrivals must then absorb these delays by path stretching and adjusting their speed, resulting in unplanned fuel consumption. However, these delays are often not distributed evenly. As a result, some arrival fixes experience severe delays while, similar to the runway systems, the other arrival fixes might experience no delays at all. The goal of this thesis is to develop a combined optimization approach for terminal airspace flow management that assigns a TRACON boundary fix and a runway to each flight while minimizing the required fuel burn and emissions. The approach lessens the severity of terminal capacity shortage caused by and imbalance of traffic demand by shunting flights from current positions to alternate runways. This is done by considering every possible path combination. To attempt to solve the congestion of the terminal airspace at both runways and arrival fixes, this research focuses on two sequential optimizations. The fix assignments are dealt with by considering, simultaneously, the capacity constraints of fixes and runways as well as the fuel consumption and emissions of each flight. The research also develops runway assignments with runway scheduling such that the total emissions produced in the terminal area and on the airport surface are minimized. The two-stage sequential framework is also extended to en route airspace. When en route airspace loses its capacity for any reason, e.g. severe weather condition, air traffic controllers and flight operators plan flight schedules together based on the given capacity limit, thereby maximizing en route throughput and minimizing flight operators' costs. However, the current methods have limitations due to the lacks of consideration of the combinatorial nature of air traffic flow management decision. One of the initial attempts to overcome these limitations is the Collaborative Trajectory Options Program (CTOP), which will be initiated soon by the Federal Aviation Administration (FAA). The developed two-stage combinatorial optimization framework fits this CTOP perfectly from the flight operator's perspective. The first stage is used to find an optimal slot allocation for flights under satisfying the ration by schedule (RBS) algorithm of the FAA. To solve the formulated first stage problem efficiently, two different solution methodologies, a heuristic algorithm and a modified branch and bound algorithm, are presented. Then, flights are assigned to the resulting optimized slots in the second stage so as to minimize the flight operator's costs.
dc.description.degree	Ph.D.
dc.format.mimetype	application/pdf
dc.identifier.uri	http://hdl.handle.net/1853/53500
dc.language.iso	en_US
dc.publisher	Georgia Institute of Technology
dc.subject	Air traffic control
dc.subject	Flow management
dc.subject	Operational research
dc.subject	Optimization
dc.subject	Air transportation management
dc.subject	Linear program
dc.subject	Mixed integer program
dc.subject	Integer program
dc.subject	Terminal airspace
dc.subject	En route airspace
dc.subject	CTOP
dc.subject	Collaborative trajectory options program
dc.subject	CDM
dc.subject	Collaborative decision making
dc.subject	Runway assignment
dc.subject	Fix assignment
dc.subject	Arrival fix
dc.subject	Departure fix
dc.subject	Runway scheduling
dc.title	Two-stage combinatorial optimization framework for air traffic flow management under constrained capacity
dc.type	Text
dc.type.genre	Dissertation
dspace.entity.type	Publication
local.contributor.corporatename	College of Engineering
local.contributor.corporatename	Daniel Guggenheim School of Aerospace Engineering
local.relation.ispartofseries	Doctor of Philosophy with a Major in Aerospace Engineering
relation.isOrgUnitOfPublication	7c022d60-21d5-497c-b552-95e489a06569
relation.isOrgUnitOfPublication	a348b767-ea7e-4789-af1f-1f1d5925fb65
relation.isSeriesOfPublication	f6a932db-1cde-43b5-bcab-bf573da55ed6
thesis.degree.level	Doctoral