자료유형 | 학위논문 |
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서명/저자사항 | Inverse Optimization, Incentive Design and Healthcare Policy. |
개인저자 | Siddiq, Auyon. |
단체저자명 | University of California, Berkeley. Industrial Engineering & Operations Research. |
발행사항 | [S.l.]: University of California, Berkeley., 2018. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
형태사항 | 155 p. |
기본자료 저록 | Dissertation Abstracts International 80-01B(E). Dissertation Abstract International |
ISBN | 9780438323933 |
학위논문주기 | Thesis (Ph.D.)--University of California, Berkeley, 2018. |
일반주기 |
Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
Adviser: Zuo-Jun Shen. |
요약 | 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 |
요약 | 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 |
요약 | 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 |
요약 | 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 |
일반주제명 | Operations research. Statistics. |
언어 | 영어 |
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: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |