Best Principal Submatrix Selection for the Maximum Entropy Sampling Problem: Scalable Algorithms and Performance Guarantees
Published Online:30 May 2023https://doi.org/10.1287/opre.2023.2488
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Volume 72, Issue 2
March-April 2024
Pages iii-vi, 425-870, C2-C3
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- Received:January 25, 2020
- Accepted:April 14, 2023
- Published Online:May 30, 2023
Copyright © 2023, INFORMS
Cite as
Yongchun Li, Weijun Xie (2023) Best Principal Submatrix Selection for the Maximum Entropy Sampling Problem: Scalable Algorithms and Performance Guarantees. Operations Research 72(2):493-513.
https://doi.org/10.1287/opre.2023.2488
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Valuable comments from Prof. Jon Lee from the University of Michigan, the editors, and anonymous reviewers are gratefully appreciated. The authors also thank Prof. Kurt Anstreicher from the University of Iowa for providing the numerical instances.
