Title
Smoothed penalty algorithms for optimization of nonlinear models
Abstract
We introduce an algorithm for solving nonlinear optimization problems with general equality and box constraints. The proposed algorithm is based on smoothing of the exact l 1-penalty function and solving the resulting problem by any box-constraint optimization method. We introduce a general algorithm and present theoretical results for updating the penalty and smoothing parameter. We apply the algorithm to optimization problems for nonlinear traffic network models and report on numerical results for a variety of network problems and different solvers for the subproblems.
Year
DOI
Venue
2007
10.1007/s10589-007-9011-6
Comp. Opt. and Appl.
Keywords
Field
DocType
Penalty methods,Traffic networks,Non-convex optimization methods
Continuous optimization,Derivative-free optimization,Mathematical optimization,Global optimization,Meta-optimization,Nonlinear programming,Algorithm,Multi-swarm optimization,Optimization problem,Mathematics,Penalty method
Journal
Volume
Issue
ISSN
37
2
0926-6003
Citations 
PageRank 
References 
7
0.57
14
Authors
4
Name
Order
Citations
PageRank
michael herty1657.10
A. Klar2203.61
A. Singh3428.59
P. Spellucci4697.19