Extended cutting plane method for a class of nonsmooth nonconvex MINLP problems

A1 Journal article (refereed)


Internal Authors/Editors


Publication Details

List of Authors: Ville-Pekka Eronen, Marko M. Mäkelä, Tapio Westerlund
Publisher: TAYLOR & FRANCIS LTD
Publication year: 2015
Journal: Optimization
Journal acronym: OPTIMIZATION
Volume number: 64
Issue number: 3
Start page: 641
End page: 661
Number of pages: 21
ISSN: 0233-1934
eISSN: 1029-4945


Abstract

In this article, a generalization of the ECP algorithm to cover a class of nondifferentiable Mixed-Integer NonLinear Programming problems is studied. In the generalization constraint functions are required to be -pseudoconvex instead of pseudoconvex functions. This enables the functions to be nonsmooth. The objective function is first assumed to be linear but also -pseudoconvex case is considered. Furthermore, the gradients used in the ECP algorithm are replaced by the subgradients of Clarke subdifferential. With some additional assumptions, the resulting algorithm shall be proven to converge to a global minimum.


Keywords

alpha ECP, extended cutting plane algorithm, generalized convexity, mixed-integer programming, nonsmooth MINLP, nonsmooth optimization, pseudoconvex function, subgradient

Last updated on 2019-23-09 at 04:06