Journal article
Using continuous nonlinear relaxations to solve. constrained maximum-entropy sampling problems
Mathematical programming, Vol.85(2), pp.221-240
06/01/1999
DOI: 10.1007/s101070050055
Abstract
We consider a new nonlinear relaxation for the Constrained Maximum-Entropy Sampling Problem the problem of choosing the s × s principal submatrix with maximal determinant from a given n × n positive definite matrix, subject to linear constraints. We implement a branch-and-bound algorithm for the problem, using the new relaxation. The performance on test problems is far superior to a previous implementation using an eigenvalue-based relaxation. A parallel implementation of the algorithm exhibits approximately linear speed-up for up to 8 processors, and has successfully solved problem instances that were heretofore intractable. © Springer-Verlag 1999.
Details
- Title: Subtitle
- Using continuous nonlinear relaxations to solve. constrained maximum-entropy sampling problems
- Creators
- Kurt M. Anstreicher - University of IowaMarcia Fampa - University of IowaJon Lee - University of KentuckyJoy Williams - University of Kentucky
- Resource Type
- Journal article
- Publication Details
- Mathematical programming, Vol.85(2), pp.221-240
- DOI
- 10.1007/s101070050055
- ISSN
- 0025-5610
- eISSN
- 1436-4646
- Language
- English
- Date published
- 06/01/1999
- Academic Unit
- Business Analytics; Industrial and Systems Engineering; Computer Science
- Record Identifier
- 9984380398002771
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