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020 ▼a 9780438017498
035 ▼a (MiAaPQ)AAI10786121
035 ▼a (MiAaPQ)purdue:22426
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 629.1
1001 ▼a Chen, Jun.
24510 ▼a Computational Optimization of Networks of Dynamical Systems Under Uncertainties: Application to the Air Transportation System.
260 ▼a [S.l.] : ▼b Purdue University., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 131 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
500 ▼a Adviser: Dengfeng Sun.
5021 ▼a Thesis (Ph.D.)--Purdue University, 2018.
520 ▼a 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
520 ▼a 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
520 ▼a 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
520 ▼a 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,
590 ▼a School code: 0183.
650 4 ▼a Aerospace engineering.
690 ▼a 0538
71020 ▼a Purdue University. ▼b Aeronautics and Astronautics.
7730 ▼t Dissertation Abstracts International ▼g 79-10B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0183
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997337 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자