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Algorithms and Software for Convex Mixed Integer Nonlinear Programs

Pierre Bonami 1, Mustafa Kilinç 2, Jeff Linderoth 2

(2009-10-07)

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

Subject

:

Computer Science/Operations Research Mathematics/Optimization and Control

Keyword(s): Mixed Integer Nonlinear Programming – Branch and Bound

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From: Pierre Bonami <>

Submitted on: Thursday, 15 October 2009 13:13:29

Updated on: Thursday, 15 October 2009 16:51:57