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020 ▼a 9780438323933
035 ▼a (MiAaPQ)AAI10807833
035 ▼a (MiAaPQ)berkeley:17735
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 658
1001 ▼a Siddiq, Auyon.
24510 ▼a Inverse Optimization, Incentive Design and Healthcare Policy.
260 ▼a [S.l.] : ▼b University of California, Berkeley., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 155 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
500 ▼a Adviser: Zuo-Jun Shen.
5021 ▼a Thesis (Ph.D.)--University of California, Berkeley, 2018.
520 ▼a This dissertation presents mathematical models and algorithms that draw from optimization and statistics and are motivated by practical problems in operations management. We discuss theoretical properties of the proposed models as well as their
520 ▼a In Chapter 2, we address the problem of building models of agent behavior from observational data regarding the agent's decisions. Concretely, we consider the inverse optimization problem, which refers to the estimation of unknown model paramete
520 ▼a In Chapter 3, we employ an inverse optimization approach to redesign a class of Medicare contracts. We formulate the existing contract between Medicare and a provider as a principal-agent model. We then propose an alternate contract, which we sh
520 ▼a In Chapter 4, we propose a data-driven modeling approach to facility location in a setting where the location of demand points is subject to uncertainty. The model is motivated by the problem of placing automated external defibrillators in publi
590 ▼a School code: 0028.
650 4 ▼a Operations research.
650 4 ▼a Statistics.
690 ▼a 0796
690 ▼a 0463
71020 ▼a University of California, Berkeley. ▼b Industrial Engineering & Operations Research.
7730 ▼t Dissertation Abstracts International ▼g 80-01B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0028
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997785 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자