Optimization Online


Algorithms and Software for Convex Mixed Integer Nonlinear Programs

Pierre Bonami (pierre.bonami***at***lif.univ-mrs.fr)
Mustafa Kılınç (kilinc***at***wisc.edu)
Jeff Linderoth (linderoth***at***wisc.edu)

Abstract: 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.

Keywords: Mixed Integer Nonlinear Programming – Branch and Bound

Category 1: Integer Programming ((Mixed) Integer Nonlinear Programming )

Citation: Technical Report #1664, Computer Sciences Department, University of Wisconsin-Madison, 2009.

Download: [PDF]

Entry Submitted: 10/15/2009
Entry Accepted: 10/15/2009
Entry Last Modified: 10/15/2009

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