Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Software for Data-Based Stochastic Programming Using Bootstrap Estimation. |
| Συγγραφείς: |
Chen, Xiaotie1 (AUTHOR) xtjchen@ucdavis.edu, Woodruff, David L.2 (AUTHOR) dlwoodruff@ucdavis.edu |
| Πηγή: |
INFORMS Journal on Computing. Nov/Dec2023, Vol. 35 Issue 6, p1218-1224. 7p. |
| Θεματικοί όροι: |
*Data libraries, *Computer software, Software development tools, Confidence intervals, Stochastic programming |
| Περίληψη: |
We describe software for stochastic programming that uses only sampled data to obtain both a consistent sample-average solution and a consistent estimate of confidence intervals for the optimality gap using bootstrap and bagging. The underlying distribution whence the samples come is not required. History: Accepted by Ted Ralphs, Area Editor for Software Tools. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0253) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2022.0253). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: |
Business Source Index |