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

Andreas Lundell, Jan Kronqvist

Research output: Chapter in Book/Conference proceedingConference contributionScientificpeer-review

Abstract

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.
Original languageUndefined/Unknown
Title of host publicationProceedings LeGO : 14th International Global Optimization Workshop : Leiden, the Netherlands, 18-21 September 2018
EditorsMichael T. M. Emmerich, André H. Deutz, Sander C. Hille, Yaroslav D. Sergeyev
PublisherAmerican Institute of Physics
Pages
Number of pages4
ISBN (Print)978-0-7354-1798-4
DOIs
Publication statusPublished - 2019
MoE publication typeA4 Article in a conference publication
EventInternational Global Optimization Workshop - LeGO 14th International Global Optimization Workshop
Duration: 18 Sep 201821 Sep 2018

Conference

ConferenceInternational Global Optimization Workshop
Period18/09/1821/09/18

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