Integrality gap minimization heuristics for binary mixed integer nonlinear programming

We present two feasibility heuristics for binary mixed integer nonlinear programming. Called integrality gap minimization algorithm (IGMA)—versions 1 and 2, our heuristics are based on the solution of integrality gap minimization problems with a space partitioning scheme defined over the integer var...

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Bibliographic Details

Published in:	Journal of global optimization Vol. 71; no. 3; pp. 593 - 612
Main Authors:	Melo, Wendel, Fampa, Marcia, Raupp, Fernanda
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.07.2018 Springer Springer Nature B.V
Subjects:	Algorithms Computer Science Heuristic Mathematics Mathematics and Statistics Mixed integer Nonlinear programming Operations Research/Decision Theory Optimization Real Functions Integrality gap minimization Solver Binary mixed integer nonlinear programming Heuristics
ISSN:	0925-5001, 1573-2916
Online Access:	Get full text
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