Journal article
Efficient Solution of Maximum-Entropy Sampling Problems
Operations research, Vol.68(6), pp.1826-1835
11/01/2020
DOI: 10.1287/opre.2019.1962
Abstract
We consider a new approach for the maximum-entropy sampling problem (MESP) that is based on bounds obtained by maximizing a function of the form ldet M(x) over linear constraints, where M(x) is linear in the n-vector x. These bounds can be computed very efficiently and are superior to all previously known bounds for MESP on most benchmark test problems. A branch-and-bound algorithm using the new bounds solves challenging instances of MESP to optimality for the first time.
Details
- Title: Subtitle
- Efficient Solution of Maximum-Entropy Sampling Problems
- Creators
- Kurt M. Anstreicher - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Operations research, Vol.68(6), pp.1826-1835
- Publisher
- Informs
- DOI
- 10.1287/opre.2019.1962
- ISSN
- 0030-364X
- eISSN
- 1526-5463
- Number of pages
- 10
- Language
- English
- Date published
- 11/01/2020
- Academic Unit
- Industrial and Systems Engineering; Computer Science; Business Analytics
- Record Identifier
- 9984380474902771
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