Title
On the complexity of finding first-order critical points in constrained nonlinear optimization.
Abstract
The complexity of finding \(\epsilon \)-approximate first-order critical points for the general smooth constrained optimization problem is shown to be no worse that \(O(\epsilon ^{-2})\) in terms of function and constraints evaluations. This result is obtained by analyzing the worst-case behaviour of a first-order short-step homotopy algorithm consisting of a feasibility phase followed by an optimization phase, and requires minimal assumptions on the objective function. Since a bound of the same order is known to be valid for the unconstrained case, this leads to the conclusion that the presence of possibly nonlinear/nonconvex inequality/equality constraints is irrelevant for this bound to apply.
Year
DOI
Venue
2014
10.1007/s10107-012-0617-9
Math. Program.
Keywords
Field
DocType
algorithms,minimization
Homotopy algorithm,Discrete mathematics,Mathematical optimization,Nonlinear system,First order,Nonlinear programming,Minification,Critical point (mathematics),Constrained optimization problem,Mathematics,Constrained optimization
Journal
Volume
Issue
ISSN
144
1-2
1436-4646
Citations 
PageRank 
References 
9
0.61
10
Authors
3
Name
Order
Citations
PageRank
Coralia Cartis145128.74
Nicholas I. M. Gould21445123.86
Philippe L. Toint31397127.90