Undercover: a primal MINLP heuristic exploring a largest sub-MIP

We present Undercover, a primal heuristic for nonconvex mixed-integer nonlinear programs (MINLPs) that explores a mixed-integer linear subproblem (sub-MIP) of a given MINLP. We solve a vertex covering problem to identify a smallest set of variables to fix, a so-called cover , such that each constrai...

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Veröffentlicht in:	Mathematical programming Jg. 144; H. 1-2; S. 315 - 346
Hauptverfasser:	Berthold, Timo, Gleixner, Ambros M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2014 Springer Nature B.V
Schlagworte:	Algorithms Analysis Calculus of Variations and Optimal Control; Optimization Combinatorics Complement Domain propagation Full Length Paper Heuristic Integer programming Linear programming Mathematical analysis Mathematical and Computational Physics Mathematical Methods in Physics Mathematical models Mathematics Mathematics and Statistics Mathematics of Computing Neighborhoods Numerical Analysis Optimization Solvers State of the art Studies Theoretical Variables 90C20 Primal heuristic Nonconvex optimization 90C30 Mixed-integer nonlinear programming Large neighborhood search 90C11 90C26 90C59 Mixed-integer quadratically constrained programming
ISSN:	0025-5610, 1436-4646
Online-Zugang:	Volltext
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