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

A1 Originalartikel i en vetenskaplig tidskrift (referentgranskad)

Interna författare/redaktörer

Publikationens författare: Ville-Pekka Eronen, Marko M. Mäkelä, Tapio Westerlund
Publiceringsår: 2015
Tidskrift: Optimization
Tidskriftsakronym: OPTIMIZATION
Volym: 64
Nummer: 3
Artikelns första sida, sidnummer: 641
Artikelns sista sida, sidnummer: 661
Antal sidor: 21
ISSN: 0233-1934
eISSN: 1029-4945


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.


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

Senast uppdaterad 2020-04-06 vid 03:47