The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
The empirical behavior of sampling methods for stochastic programming
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Citations
Cites
Rockafellar, R. T. (1970) · Princeton University Press eBooks · doi:10.1515/9781400873173 · Cited by 10,801
The Grid 2: Blueprint for a New Computing Infrastructure
Foster, I. T., & Kesselman, C. (1998) · Cited by 7,637
McKay, M. D., Beckman, R. J., & Conover, W. J. (2000) · Technometrics · doi:10.2307/1271432 · Cited by 7,415
Linear Programming and Extensions
Dantzig, G. (1963) · RAND Corporation eBooks · doi:10.7249/r366 · Cited by 5,755
Linear Programming and Extensions
Dantzig, G. (1963) · Princeton University Press eBooks · doi:10.1515/9781400884179 · Cited by 2,713
Large Sample Properties of Simulations Using Latin Hypercube Sampling
Stein, M. (1987) · Technometrics · doi:10.1080/00401706.1987.10488205 · Cited by 2,471
The Sample Average Approximation Method for Stochastic Discrete Optimization
Kleywegt, A. J., Shapiro, A., & Homem-de-Mello, T. (2002) · SIAM Journal on Optimization · doi:10.1137/s1052623499363220 · Cited by 1,983
Self-citationAMPL : a modeling language for mathematical programming
Fourer, R., & Kernighan, B. W. (1993) · Cited by 1,860
(1979) · Studies in Mathematics and Its Applications · doi:10.1016/s0168-2024(09)x7002-5 · Cited by 1,594
Monte Carlo bounding techniques for determining solution quality in stochastic programs
Mak, W.-K., Morton, D. P., & Wood, R. K. (1999) · Operations Research Letters · doi:10.1016/s0167-6377(98)00054-6 · Cited by 704
Cited by
The Impact of Charging Plug-In Hybrid Electric Vehicles on a Residential Distribution Grid
Clement-Nyns, K., Haesen, E., & Driesen, J. (2010) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2009.2036481 · Cited by 2,847
Shapiro, A. (2003) · Handbooks in Operations Research and Management Science · doi:10.1016/s0927-0507(03)10006-0 · Cited by 916
Self-citationAn optimal method for stochastic composite optimization
Lan, G. (2012) · Mathematical Programming · doi:10.1007/s10107-010-0434-y · Cited by 427
On Complexity of Stochastic Programming Problems
Shapiro, A., & Nemirovski, A. (2006) · Applied Optimization · doi:10.1007/0-387-26771-9_4 · Cited by 301
Self-citationMonte Carlo sampling-based methods for stochastic optimization
Homem-de-Mello, T., & Bayraksan, G. (2014) · Surveys in Operations Research and Management Science · doi:10.1016/j.sorms.2014.05.001 · Cited by 283
Metadata
- Authors
- Linderoth, J., Shapiro, A., & Wright, S.
- Venue
- Annals of Operations Research
- Published
- 2006-02
- Volume
- 142
- Issue
- 1
- Pages
- 215-241
- ISSN
- 0254-5330 (ISSN-L)
- 1572-9338
- OpenAlex
- W2000257769
- Cited by
- 425
- References
- 29
- FWCI
- 35.02
- Type
- journal article
- Language
- en
- Open access
- closed
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- Linderoth, J., Shapiro, A., & Wright, S. (2006). The empirical behavior of sampling methods for stochastic programming. Annals of Operations Research. https://doi.org/10.1007/s10479-006-6169-8
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
