A center-cut algorithm for solving convex mixed-integer nonlinear programming problems

A4 Conference proceedings


Internal Authors/Editors


Publication Details

List of Authors: Jan Kronqvist, Andreas Lundell, Tapio Westerlund
Editors: Antonio Espuña, Moisès Graells, Luis Puigjaner
Publication year: 2017
Publisher: Elsevier
Book title: 27 European Symposium on Computer Aided Process Engineering
Title of series: Computer Aided Chemical Engineering
Volume number: 40
Start page: 2131
End page: 2136
ISBN: 978-0-444-63965-3
eISBN: 9780444639707
ISSN: 1570-7946


Abstract

    In this paper, we present a new algorithm for solving convex mixed-integer nonlinear programming problems. Similarly to other linearization-based methods, the algorithm generates a polyhedral approximation of the feasible region. The main idea behind the algorithm is to use a different approach for obtaining trial solutions. Here trial solutions are chosen as a center of the polyhedral approximation. By choosing the trial solutions as such, the algorithm is more likely to obtain feasible solutions within only a few iterations, compared to the approach of choosing trial solutions as the minimizer of a linear approximation of the problem. The algorithm can be used both as a technique for finding the optimal solution or as a technique for quickly finding a feasible solution to a given problem. The algorithm has been applied to some challenging test problems, and for these the algorithm is able to find a feasible solution within only a few iterations.


    Last updated on 2019-18-10 at 03:58