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Algorithms and Software for Convex Mixed Integer Nonlinear Programs
Pierre Bonami 1, Mustafa Kilinç 2, Jeff Linderoth 2
(07/10/2009)

This paper provides a survey of recent progress and software for solving mixed integer nonlinear programs (MINLP) wherein the objective and constraints are defined by convex functions and integrality restrictions are imposed on a subset of the decision variables. Convex MINLPs have received sustained attention in very years. By exploiting analogies to the case of well-known techniques for solving mixed integer linear programs and incorporating these techniques into the software, significant improvements have been made in our ability to solve the problems.
1 :  Laboratoire d'informatique Fondamentale de Marseille (LIF)
CNRS : UMR6166 – Université de la Méditerranée - Aix-Marseille II – Université de Provence - Aix-Marseille I
2 :  Department of Industrial and Systems Engineering [Wisconsin-Madison] (ISyE)
University of Wisconsin-Madison
Informatique/Recherche opérationnelle

Mathématiques/Optimisation et contrôle
Mixed Integer Nonlinear Programming – Branch and Bound
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