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Scenarios and Policy Aggregation in Optimization Under Uncertainty
Abstract
A common approach in coping with multiperiod optimization problems under uncertainty where statistical information is not really enough to support a stochastic programming model, has been to set up and analyze a number of scenarios. The aim then is to identify trends and essential features on which a robust decision policy can be based. This paper develops for the first time a rigorous algorithmic procedure for determining such a policy in response to any weighting of the scenarios. The scenarios are bundled at various levels to reflect the availability of information, and iterative adjustments are made to the decision policy to adapt to this structure and remove the dependence on hindsight.
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Cited by
Boyd, S., Parikh, N., Chu, E., Peleato, B., & Eckstein, J. (2011) · Foundations and Trends® in Machine Learning · doi:10.1561/2200000016 · Cited by 17,075
Pyomo — Optimization Modeling in Python
Bynum, M. L., Hackebeil, G. A., Hart, W. E., Laird, C. D., Nicholson, B. L., Siirola, J. D., Watson, J.-P., & Woodruff, D. L. (2021) · Springer Optimization and Its Applications · doi:10.1007/978-3-030-68928-5 · Cited by 806
Reserve Requirements for Wind Power Integration: A Scenario-Based Stochastic Programming Framework
Papavasiliou, A., Oren, S. S., & O'Neill, R. P. (2011) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2011.2121095 · Cited by 580
Formalizing best practice for energy system optimization modelling
DeCarolis, J., Daly, H., Dodds, P., Keppo, I., Li, F., McDowall, W., Pye, S., Strachan, N., Trutnevyte, E., Usher, W., et al. (2017) · Applied Energy · doi:10.1016/j.apenergy.2017.03.001 · Cited by 389
Metadata
- Authors
- Rockafellar, R. T., & Wets, R. J.-B.
- Venue
- Mathematics of Operations Research
- Published
- 1991-02
- Volume
- 16
- Issue
- 1
- Pages
- 119-147
- ISSN
- 0364-765X (ISSN-L)
- 1526-5471
- OpenAlex
- W1969007958
- Cited by
- 1,340
- References
- 0
- FWCI
- 37.85
- Type
- journal article
- Language
- en
- Open access
- closed
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- Rockafellar, R. T., & Wets, R. J.-B. (1991). Scenarios and Policy Aggregation in Optimization Under Uncertainty. Mathematics of Operations Research. https://doi.org/10.1287/moor.16.1.119
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
