| dc.contributor.author | Doan, Xuan Vinh | |
| dc.contributor.author | Natarajan, Karthik | |
| dc.contributor.author | Teo, Chung-Piaw | |
| dc.contributor.author | Bertsimas, Dimitris J | |
| dc.date.accessioned | 2012-04-04T15:25:39Z | |
| dc.date.available | 2012-04-04T15:25:39Z | |
| dc.date.issued | 2010-08 | |
| dc.date.submitted | 2009-04 | |
| dc.identifier.issn | 0364-765X | |
| dc.identifier.issn | 1526-5471 | |
| dc.identifier.uri | http://hdl.handle.net/1721.1/69922 | |
| dc.description.abstract | We propose a semidefinite optimization (SDP) model for the class of minimax two-stage stochastic linear optimization problems with risk aversion. The distribution of second-stage random variables belongs to a set of multivariate distributions with known first and second moments. For the minimax stochastic problem with random objective, we provide a tight SDP formulation. The problem with random right-hand side is NP-hard in general. In a special case, the problem can be solved in polynomial time. Explicit constructions of the worst-case distributions are provided. Applications in a production-transportation problem and a single facility minimax distance problem are provided to demonstrate our approach. In our experiments, the performance of minimax solutions is close to that of data-driven solutions under the multivariate normal distribution and better under extremal distributions. The minimax solutions thus guarantee to hedge against these worst possible distributions and provide a natural distribution to stress test stochastic optimization problems under distributional ambiguity. | en_US |
| dc.description.sponsorship | Singapore-MIT Alliance for Research and Technology | en_US |
| dc.description.sponsorship | National University of Singapore. Dept. of Mathematics | en_US |
| dc.language.iso | en_US | |
| dc.publisher | Institute for Operations Research and the Management Sciences | en_US |
| dc.relation.isversionof | http://dx.doi.org/10.1287/moor.1100.0445 | en_US |
| dc.rights | Creative Commons Attribution-Noncommercial-Share Alike 3.0 | en_US |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/ | en_US |
| dc.source | Prof. Bertsimas via Alex Caracuzzo | en_US |
| dc.title | Models for Minimax Stochastic Linear Optimization Problems with Risk Aversion | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Bertsimas, D. et al. “Models for Minimax Stochastic Linear Optimization Problems with Risk Aversion.” Mathematics of Operations Research 35.3 (2010): 580–602. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Operations Research Center | en_US |
| dc.contributor.department | Sloan School of Management | en_US |
| dc.contributor.approver | Bertsimas, Dimitris J. | |
| dc.contributor.mitauthor | Doan, Xuan Vinh | |
| dc.contributor.mitauthor | Bertsimas, Dimitris J. | |
| dc.relation.journal | Mathematics of Operations Research | en_US |
| dc.eprint.version | Author's final manuscript | en_US |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
| dspace.orderedauthors | Bertsimas, D.; Doan, X. V.; Natarajan, K.; Teo, C.-P. | en |
| dc.identifier.orcid | https://orcid.org/0000-0002-1985-1003 | |
| mit.license | OPEN_ACCESS_POLICY | en_US |
| mit.metadata.status | Complete | |