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Decision Modeling Framework to Minim...

Mohleji, Nandita.

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Decision Modeling Framework to Minimize Arrival Delays from Ground Delay Programs.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Decision Modeling Framework to Minimize Arrival Delays from Ground Delay Programs./
作者:	Mohleji, Nandita.
面頁冊數:	134 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-05(E), Section: B.
Contained By:	Dissertation Abstracts International77-05B(E).
標題:	Systems science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3740141
ISBN:	9781339321424

Decision Modeling Framework to Minimize Arrival Delays from Ground Delay Programs.
Mohleji, Nandita.

Decision Modeling Framework to Minimize Arrival Delays from Ground Delay Programs. - 134 p.

Source: Dissertation Abstracts International, Volume: 77-05(E), Section: B.

Thesis (Ph.D.)--The George Washington University, 2016.

Convective weather and other constraints create uncertainty in air transportation, leading to costly delays. A Ground Delay Program (GDP) is a strategy to mitigate these effects. Systematic decision support can increase GDP efficacy, reduce delays, and minimize direct operating costs. In this study, a decision analysis (DA) model is constructed by combining a decision tree and Bayesian belief network. Through a study of three New York region airports, the DA model demonstrates that larger GDP scopes that include more flights in the program, along with longer lead times that provide stakeholders greater notice of a pending program, trigger the fewest average arrival delays. These findings are demonstrated to result in a savings of up to $1,850 per flight. Furthermore, when convective weather is predicted, forecast weather confidences remain the same level or greater at least 70% of the time, supporting more strategic decision making. The DA model thus enables quantification of uncertainties and insights on causal relationships, providing support for future GDP decisions.

ISBN: 9781339321424Subjects--Topical Terms:

3168411
Systems science.

Decision Modeling Framework to Minimize Arrival Delays from Ground Delay Programs.
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520 $a Convective weather and other constraints create uncertainty in air transportation, leading to costly delays. A Ground Delay Program (GDP) is a strategy to mitigate these effects. Systematic decision support can increase GDP efficacy, reduce delays, and minimize direct operating costs. In this study, a decision analysis (DA) model is constructed by combining a decision tree and Bayesian belief network. Through a study of three New York region airports, the DA model demonstrates that larger GDP scopes that include more flights in the program, along with longer lead times that provide stakeholders greater notice of a pending program, trigger the fewest average arrival delays. These findings are demonstrated to result in a savings of up to $1,850 per flight. Furthermore, when convective weather is predicted, forecast weather confidences remain the same level or greater at least 70% of the time, supporting more strategic decision making. The DA model thus enables quantification of uncertainties and insights on causal relationships, providing support for future GDP decisions.
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