TY - JOUR
T1 - An inexact proximal method for quasiconvex minimization
AU - Papa Quiroz, E. A.
AU - Mallma Ramirez, L.
AU - Oliveira, P. R.
N1 - Publisher Copyright:
© 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.
PY - 2015/11/1
Y1 - 2015/11/1
N2 - In this paper we propose an inexact proximal point method to solve constrained minimization problems with locally Lipschitz quasiconvex objective functions. Assuming that the function is also bounded from below, lower semicontinuous and using proximal distances, we show that the sequence generated for the method converges to a stationary point of the problem.
AB - In this paper we propose an inexact proximal point method to solve constrained minimization problems with locally Lipschitz quasiconvex objective functions. Assuming that the function is also bounded from below, lower semicontinuous and using proximal distances, we show that the sequence generated for the method converges to a stationary point of the problem.
KW - Computing science
KW - Global optimization
KW - Nonlinear programming
KW - Proximal point methods
KW - Quasiconvex minimization
UR - http://www.scopus.com/inward/record.url?scp=84932199291&partnerID=8YFLogxK
U2 - 10.1016/j.ejor.2015.05.041
DO - 10.1016/j.ejor.2015.05.041
M3 - Article
AN - SCOPUS:84932199291
SN - 0377-2217
VL - 246
SP - 721
EP - 729
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 3
ER -