Exact semidefinite formulations for a class of (random and non-random) nonconvex quadratic programs
We study a class of quadratically constrained quadratic programs (QCQPs), called diagonal QCQPs , which contain no off-diagonal terms x j x k for j ≠ k , and we provide a sufficient condition on the problem data guaranteeing that the basic Shor semidefinite relaxation is exact. Our condition complem...
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| Vydané v: | Mathematical programming Ročník 181; číslo 1; s. 1 - 17 |
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| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
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Berlin/Heidelberg
Springer Berlin Heidelberg
01.05.2020
Springer Nature B.V |
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| ISSN: | 0025-5610, 1436-4646 |
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| Abstract | We study a class of quadratically constrained quadratic programs (QCQPs), called
diagonal QCQPs
, which contain no off-diagonal terms
x
j
x
k
for
j
≠
k
, and we provide a sufficient condition on the problem data guaranteeing that the basic Shor semidefinite relaxation is exact. Our condition complements and refines those already present in the literature and can be checked in polynomial time. We then extend our analysis from diagonal QCQPs to general QCQPs, i.e., ones with no particular structure. By reformulating a general QCQP into diagonal form, we establish new, polynomial-time-checkable sufficient conditions for the semidefinite relaxations of general QCQPs to be exact. Finally, these ideas are extended to show that a class of random general QCQPs has exact semidefinite relaxations with high probability as long as the number of constraints grows no faster than a fixed polynomial in the number of variables. To the best of our knowledge, this is the first result establishing the exactness of the semidefinite relaxation for random general QCQPs. |
|---|---|
| AbstractList | We study a class of quadratically constrained quadratic programs (QCQPs), called diagonal QCQPs, which contain no off-diagonal terms xjxk for j≠k, and we provide a sufficient condition on the problem data guaranteeing that the basic Shor semidefinite relaxation is exact. Our condition complements and refines those already present in the literature and can be checked in polynomial time. We then extend our analysis from diagonal QCQPs to general QCQPs, i.e., ones with no particular structure. By reformulating a general QCQP into diagonal form, we establish new, polynomial-time-checkable sufficient conditions for the semidefinite relaxations of general QCQPs to be exact. Finally, these ideas are extended to show that a class of random general QCQPs has exact semidefinite relaxations with high probability as long as the number of constraints grows no faster than a fixed polynomial in the number of variables. To the best of our knowledge, this is the first result establishing the exactness of the semidefinite relaxation for random general QCQPs. We study a class of quadratically constrained quadratic programs (QCQPs), called diagonal QCQPs , which contain no off-diagonal terms x j x k for j ≠ k , and we provide a sufficient condition on the problem data guaranteeing that the basic Shor semidefinite relaxation is exact. Our condition complements and refines those already present in the literature and can be checked in polynomial time. We then extend our analysis from diagonal QCQPs to general QCQPs, i.e., ones with no particular structure. By reformulating a general QCQP into diagonal form, we establish new, polynomial-time-checkable sufficient conditions for the semidefinite relaxations of general QCQPs to be exact. Finally, these ideas are extended to show that a class of random general QCQPs has exact semidefinite relaxations with high probability as long as the number of constraints grows no faster than a fixed polynomial in the number of variables. To the best of our knowledge, this is the first result establishing the exactness of the semidefinite relaxation for random general QCQPs. |
| Author | Ye, Yinyu Burer, Samuel |
| Author_xml | – sequence: 1 givenname: Samuel orcidid: 0000-0001-5886-458X surname: Burer fullname: Burer, Samuel email: samuel-burer@uiowa.edu organization: Department of Management Sciences, University of Iowa – sequence: 2 givenname: Yinyu surname: Ye fullname: Ye, Yinyu organization: Department of Management Science and Engineering, Institute of Computational and Mathematical Engineering, Stanford University |
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| Copyright | Springer-Verlag GmbH Germany, part of Springer Nature and Mathematical Optimization Society 2019 Mathematical Programming is a copyright of Springer, (2019). All Rights Reserved. Springer-Verlag GmbH Germany, part of Springer Nature and Mathematical Optimization Society 2019. |
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| Snippet | We study a class of quadratically constrained quadratic programs (QCQPs), called
diagonal QCQPs
, which contain no off-diagonal terms
x
j
x
k
for
j
≠
k
, and... We study a class of quadratically constrained quadratic programs (QCQPs), called diagonal QCQPs, which contain no off-diagonal terms xjxk for j≠k, and we... |
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| SubjectTerms | Approximation Calculus of Variations and Optimal Control; Optimization Combinatorics Constraints Formulations Full Length Paper Mathematical and Computational Physics Mathematical Methods in Physics Mathematical programming Mathematics Mathematics and Statistics Mathematics of Computing Numerical Analysis Optimization Polynomials Theoretical Variables |
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| Title | Exact semidefinite formulations for a class of (random and non-random) nonconvex quadratic programs |
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