Title
Inexact solution of NLP subproblems in MINLP
Abstract
In the context of convex mixed integer nonlinear programming (MINLP), we investigate how the outer approximation method and the generalized Benders decomposition method are affected when the respective nonlinear programming (NLP) subproblems are solved inexactly. We show that the cuts in the corresponding master problems can be changed to incorporate the inexact residuals, still rendering equivalence and finiteness in the limit case. Some numerical results will be presented to illustrate the behavior of the methods under NLP subproblem inexactness.
Year
DOI
Venue
2013
10.1007/s10898-012-0010-5
J. Global Optimization
Keywords
DocType
Volume
Mixed integer nonlinear programming,Outer approximation,Generalized Benders decomposition,Inexactness,Convexity
Journal
55
Issue
ISSN
Citations 
4
0925-5001
2
PageRank 
References 
Authors
0.38
11
2
Name
Order
Citations
PageRank
M. Li120.38
luis n vicente217611.24