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Computational Optimization of Networks of Dynamical Systems Under Uncertainties: Application to the Air Transportation System
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Computational Optimization of Networks of Dynamical Systems Under Uncertainties: Application to the Air Transportation System. |
| 개인저자 | Chen, Jun. |
| 단체저자명 | Purdue University. Aeronautics and Astronautics. |
| 발행사항 | [S.l.]: Purdue University., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 131 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-10B(E). Dissertation Abstract International |
| ISBN | 9780438017498 |
| 학위논문주기 | Thesis (Ph.D.)--Purdue University, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
Adviser: Dengfeng Sun. |
| 요약 | To efficiently balance traffic demand and capacity, optimization of air traffic management relies on accurate predictions of future capacities, which are inherently uncertain due to weather forecast. This dissertation presents a novel computatio |
| 요약 | First, a chance constrained model for a single airport ground holding problem is proposed with the concept of service level, which provides a event-oriented performance criterion for uncertainty. With the validated advantage on robust optimal pl |
| 요약 | Following the similar idea, the chance constrained model is extended to formulate a traffic flow management problem under probabilistic sector capacities, which is derived from a previous deterministic linear model. The nonlinearity from the cha |
| 요약 | Finally, the specially designed architecture of the convex approximation provides massive independent internal approximation processes, which makes parallel computing to be suitable. A distributed computing framework is designed based on Spark, |
| 일반주제명 | Aerospace engineering. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
