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Linear Programming under Uncertainty
Abstract
The essential character of the general models under consideration is that activities are divided into two or more stages. The quantities of activities in the first stage are the only ones that are required to be determined; those in the second (or later) stages can not be determined in advance since they depend on the earlier stages and the random or uncertain demands which occur on or before the latter stage. It is important to note that the set of activities are assumed to be complete in the sense that, whatever be the choice of activities in the earlier stages (consistent with the restrictions applicable to their stage), there is a possible choice of activities in the latter stages. In other words it is not possible to get in a position where the programming problem admits of no solution.
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Cited by
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Nguyen, A.-T., Reiter, S., & Rigo, P. (2014) · Applied Energy · doi:10.1016/j.apenergy.2013.08.061 · Cited by 1,379
Uncertain convex programs: randomized solutions and confidence levels
Calafiore, G., & Campi, M. C. (2005) · Mathematical Programming · doi:10.1007/s10107-003-0499-y · Cited by 659
Collins, S., Deane, J. P., Poncelet, K., Panos, E., Pietzcker, R. C., Delarue, E., & Ó Gallachóir, B. P. (2017) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2017.03.090 · Cited by 282
Zubo, R. H. A., Mokryani, G., Rajamani, H.-S., Aghaei, J., Niknam, T., & Pillai, P. (2017) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.10.036 · Cited by 218
Theory and applications of robust optimization
Bertsimas, D., Brown, D. B., & Caramanis, C. (2011) · SIAM Review · doi:10.1137/080734510 · Cited by 134
Metadata
- Authors
- Dantzig, G. B.
- Venue
- Management Science
- Published
- 1955-04
- Volume
- 1
- Issue
- 3-4
- Pages
- 197-206
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W4251495539
- Cited by
- 1,225
- References
- 0
- FWCI
- 0.66
- Type
- journal article
- Language
- en
- Open access
- closed
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- Dantzig, G. B. (1955). Linear Programming under Uncertainty. Management Science. https://doi.org/10.1287/mnsc.1.3-4.197
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