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020 ▼a 9780438048003
035 ▼a (MiAaPQ)AAI10816009
035 ▼a (MiAaPQ)princeton:12533
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 660
1001 ▼a Matthews, Logan Ryan.
24510 ▼a Advancing Robust Optimization for Process Systems Engineering Applications.
260 ▼a [S.l.] : ▼b Princeton University., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 321 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
500 ▼a Adviser: Ioannis G. Kevrekidis.
5021 ▼a Thesis (Ph.D.)--Princeton University, 2018.
520 ▼a Robust optimization is a popular method for incorporating parameter uncertainty into optimization models. Whether parameters represent the price of a feedstock or product, the operability of an edge in a network, or length of time required for a
520 ▼a This dissertation seeks to expand the theory and application of robust optimization for problems in process systems engineering. Theoretically, this focuses on decreasing the conservatism and increasing the applicability of robust optimization m
520 ▼a Robust optimization is also shown to be effective in two major application areas. First, it is applied to process synthesis and global optimization of liquid transportation fuel refineries from natural gas and biomass, when feedstock prices, pro
590 ▼a School code: 0181.
650 4 ▼a Chemical engineering.
690 ▼a 0542
71020 ▼a Princeton University. ▼b Chemical and Biological Engineering.
7730 ▼t Dissertation Abstracts International ▼g 79-10B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0181
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998214 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자