Quadratic programs with hollows

Let F be a quadratically constrained, possibly nonconvex, bounded set, and let E 1 , … , E l denote ellipsoids contained in F with non-intersecting interiors. We prove that minimizing an arbitrary quadratic q ( · ) over G : = F \ ∪ k = 1 ℓ int ( E k ) is no more difficult than minimizing q ( · ) ove...

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Veröffentlicht in:Mathematical programming Jg. 170; H. 2; S. 541 - 553
Hauptverfasser: Yang, Boshi, Anstreicher, Kurt, Burer, Samuel
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2018
Springer Nature B.V
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ISSN:0025-5610, 1436-4646
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Zusammenfassung:Let F be a quadratically constrained, possibly nonconvex, bounded set, and let E 1 , … , E l denote ellipsoids contained in F with non-intersecting interiors. We prove that minimizing an arbitrary quadratic q ( · ) over G : = F \ ∪ k = 1 ℓ int ( E k ) is no more difficult than minimizing q ( · ) over F in the following sense: if a given semidefinite-programming (SDP) relaxation for min { q ( x ) : x ∈ F } is tight, then the addition of l linear constraints derived from E 1 , … , E l yields a tight SDP relaxation for min { q ( x ) : x ∈ G } . We also prove that the convex hull of { ( x , x x T ) : x ∈ G } equals the intersection of the convex hull of { ( x , x x T ) : x ∈ F } with the same l linear constraints. Inspired by these results, we resolve a related question in a seemingly unrelated area, mixed-integer nonconvex quadratic programming.
Bibliographie:ObjectType-Article-1
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ISSN:0025-5610
1436-4646
DOI:10.1007/s10107-017-1157-0