Integration of polyhedral outer approximation algorithms with MIP solvers through callbacks and lazy constraints

A4 Conference proceedings

Internal Authors/Editors

Publication Details

List of Authors: Andreas Lundell, Jan Kronqvist
Editors: Michael T. M. Emmerich, André H. Deutz, Sander C. Hille, Yaroslav D. Sergeyev
Place: Melville, NY
Publication year: 2019
Journal: AIP Conference Proceedings
Publisher: American Institute of Physics
Book title: Proceedings LeGO : 14th International Global Optimization Workshop : Leiden, the Netherlands, 18-21 September 2018
Journal acronym: AIP CONF PROC
Title of series: AIP conference proceedings
Volume number: 2070
Number of pages: 4
ISBN: 978-0-7354-1798-4
ISSN: 0094-243X


In this paper, it is explained how algorithms for convex mixed-integer nonlinear programming (MINLP) based on polyhedral outer approximation (P0A) can be integrated with mixed-integer programming (MIP) solvers through callbacks and lazy constraints. Through this integration, a new approach utilizing a single branching tree is obtained which reduces the overhead required when rebuilding the branching tree in the MIP solver due to the continuous addition of linear constraints approximating the nonlinear feasible region of the MINLP problem. The result is an efficient strategy for implementing a POA utilized by the Supporting llyperplane Optimization Toolkit (SHOT) solver.

Last updated on 2020-02-04 at 05:10