상세정보
Export to Refworks부가기능
Solution Methods and Bounds for Two-stage Risk-neutral and Multistage Risk-averse Stochastic Mixed-integer Programs with Applications in Energy and Manufacturing
상세 프로파일
| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Solution Methods and Bounds for Two-stage Risk-neutral and Multistage Risk-averse Stochastic Mixed-integer Programs with Applications in Energy and Manufacturing. |
| 개인저자 | Guo, Ge. |
| 단체저자명 | Iowa State University. Industrial and Manufacturing Systems Engineering. |
| 발행사항 | [S.l.]: Iowa State University., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 113 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-11B(E). Dissertation Abstract International |
| ISBN | 9780438072909 |
| 학위논문주기 | Thesis (Ph.D.)--Iowa State University, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.
Adviser: Sarah M. Ryan. |
| 요약 | This dissertation presents an integrated method for solving stochastic mixed-integer programs, develops a lower bounding approach for multistage risk-averse stochastic mixed-integer programs, and proposes an optimization formulation for mixed-mo |
| 요약 | It is well known that a stochastic mixed-integer program is difficult to solve due to its non-convexity and stochastic factors. The scenario decomposition algorithms display computational advantage when dealing with a large number of possible re |
| 요약 | In many applications, the decision makers are risk-averse and are more concerned with large losses in the worst scenarios than with average performance. The PH algorithm can serve as a time-efficient heuristic for risk-averse stochastic mixed-in |
| 요약 | The existing optimization formulations for MMALS problems do not consider many real-world uncertainty factors such as timely part delivery and material quality. In addition, real-time sequencing decisions are required to deal with inevitable dis |
| 요약 | Computational studies show that the integration of PH helps DD to reduce the run-time significantly, and the lower bounding approach can obtain convergent and tight lower bounds to help PH evaluate quality of solutions. The PH algorithm and the |
| 일반주제명 | Industrial engineering. Operations research. Statistics. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
