Solving maximum-entropy sampling problems using factored masks

Authors:
Samuel Burer;Jon Lee
Affiliations:
University of Iowa, Department of Management Sciences, 52242, Iowa City, IA, USA;IBM, Department of Mathematical Sciences, T.J. Watson Research Center, 10598, Yorktown Heights, NY, USA
Venue:
Mathematical Programming: Series A and B
Year:
2007

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Abstract

We present a practical approach to Anstreicher and Lee’s masked spectral bound for maximum-entropy sampling, and we describe favorable results that we have obtained with a Branch-and-Bound algorithm based on our approach. By representing masks in factored form, we are able to easily satisfy a semidefiniteness constraint. Moreover, this representation allows us to restrict the rank of the mask as a means for attempting to practically incorporate second-order information.