The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Is optimization optimistically biased?
Abstract
Does optimization systematically lead to solutions that appear better than they actually turn out to be when implemented? The answer can be yes if there are errors in estimating objective function coefficients. Even if such errors are unbiased, the calculated value of the objective function for the optimal solution will, in an expected value sense, overstate that solution's true performance. This presupposes that errors in the constraint set are relatively unimportant. The existence of such a bias is shown by proof; Monte Carlo simulations of two realistic water resources optimization problems show its significance for water planners. The most important implication is that the estimated net benefits of model solutions may be exaggerated compared to existing water systems, whose performance is generally known with more accuracy.
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“, hourly resolution models) tend to choose “optimal” settings with little room for error [11].”
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Metadata
- Authors
- Hobbs, B. F., & Hepenstal, A.
- ORCID
- Hobbs, Benjamin F.
- Venue
- Water Resources Research
- Publisher
- American Geophysical Union (AGU)
- Published
- 1989-02
- Volume
- 25
- Issue
- 2
- Pages
- 152-160
- ISSN
- 0043-1397 (ISSN-L)
- 1944-7973
- OpenAlex
- W1990277704
- Cited by
- 33
- References
- 24
- Citations by year
- 2023: 3 · 2022: 2 · 2021: 2 · 2020: 1 · 2019: 3 · 2018: 1 · 2017: 1 · 2015: 2 · 2012: 3
- FWCI
- 6.55
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Water Resources Research (publishedVersion)
- Topics
- Physical Sciences › Environmental Science › Water Science and Technology › Water resources management and optimization
- Social Sciences › Decision Sciences › Management Science and Operations Research › Optimization and Mathematical Programming
- Social Sciences › Decision Sciences › Management Science and Operations Research › Risk and Portfolio Optimization
- Keywords
- water resources planning, water allocation model
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