Algorithms and Software for Convex Mixed Integer Nonlinear Programs

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Bonami, Pierre
Kilinc, Mustafa
Linderoth, Jeff

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Technical Report

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University of Wisconsin-Madison Department of Computer Sciences

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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.

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TR1664

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