Convex relaxations of non-convex mixed integer quadratically constrained programs: extended formulations

This paper addresses the problem of generating strong convex relaxations of Mixed Integer Quadratically Constrained Programming (MIQCP) problems. MIQCP problems are very difficult because they combine two kinds of non- convexities: integer variables and non-convex quadratic constraints. To produce s...

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Vydané v:	Mathematical programming Ročník 124; číslo 1-2; s. 383 - 411
Hlavní autori:	Saxena, Anureet, Bonami, Pierre, Lee, Jon
Médium:	Journal Article Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer-Verlag 01.07.2010 Springer Springer Nature B.V
Predmet:	Applied sciences Approximation Calculus of Variations and Optimal Control; Optimization Combinatorics Constraints Cutting Eigenvalues Eigenvectors Exact sciences and technology Full Length Paper Inequality Linear equations Linear programming Mathematical analysis Mathematical and Computational Physics Mathematical Methods in Physics Mathematical models Mathematical programming Mathematics Mathematics and Statistics Mathematics of Computing Mixed integer Numerical Analysis Operational research and scientific management Operational research. Management science Optimization Programming Theoretical global optimization 90C26 Nonconvex programming Non convex programming Eigenvector Constraint satisfaction Global optimum Mixed integer programming Quadratic programming Modeling Cutting plane method Convex programming Cut generation Integer programming Disjunction Disjunctive programming Eigenvalue problem Convexity Non convex analysis
ISSN:	0025-5610, 1436-4646
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