RT Journal Article
T1 On decomposition and multiobjective-based column and disjunctive cut generation for MINLP.
A1 Muts, Pavlo
A1 Nowak, Ivo
A1 Hendrix, Eligius María Theodorus
K1 Programación no lineal
AB Most industrial optimization problems are sparse and can be formulated as block- separable mixed-integer nonlinear programming (MINLP) problems, defined by linking low-dimensional sub-problems by (linear) coupling constraints. This paper investigates the potential of using decomposition and a novel multiobjective-based column and cut generation approach for solving nonconvex block-separable MIN- LPs, based on the so-called resource-constrained reformulation. Based on this approach, two decomposition-based inner- and outer-refinement algorithms are presented and preliminary numerical results with nonconvex MINLP instances are reported.
PB Springer Nature
YR 2020
FD 2020
LK https://hdl.handle.net/10630/35173
UL https://hdl.handle.net/10630/35173
LA eng
NO Muts, P., Nowak, I. and Hendrix, E.M.T.  (2021), On decomposition and multiobjective-based column and disjunctive cut generation for MINLP, Optimization and Engineering, 22, 1389-1418
NO Open Access funding enabled and organized by Projekt DEAL.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026