Compact mixed-integer programming formulations in quadratic optimization

We present a technique for producing valid dual bounds for nonconvex quadratic optimization problems. The approach leverages an elegant piecewise linear approximation for univariate quadratic functions due to Yarotsky (Neural Netw 94:103–114, 2017), formulating this (simple) approximation using mixe...

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Bibliographic Details
Published in:	Journal of global optimization Vol. 84; no. 4; pp. 869 - 912
Main Authors:	Beach, Benjamin, Hildebrand, Robert, Huchette, Joey
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.12.2022 Springer Springer Nature B.V
Subjects:	Approximation Computer Science Continuity (mathematics) Integer programming Linear programming Mathematics Mathematics and Statistics Mixed integer Operations Research/Decision Theory Optimization Perturbation methods Quadratic equations Real Functions Tightness Gray Code Nonconvex optimization Quadratic optimization Mixed-integer programming
ISSN:	0925-5001, 1573-2916
Online Access:	Get full text
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