An exact penalization viewpoint of constrained optimization
SIAM Journal on Control and Optimization
Representations of quasi-Newton matrices and their use in limited memory methods
Mathematical Programming: Series A and B
A mathematical model of traffic flow on a network of unidirectional roads
SIAM Journal on Mathematical Analysis
A limited memory algorithm for bound constrained optimization
SIAM Journal on Scientific Computing
Smoothing methods for convex inequalities and linear complementarity problems
Mathematical Programming: Series A and B
The symmetric eigenvalue problem
The symmetric eigenvalue problem
SSVM: A Smooth Support Vector Machine for Classification
Computational Optimization and Applications
Modeling, Simulation, and Optimization of Traffic Flow Networks
SIAM Journal on Scientific Computing
Combinatorial and Continuous Models for the Optimization of Traffic Flows on Networks
SIAM Journal on Optimization
Penalty Techniques for State Constrained Optimal Control Problems with the Wave Equation
SIAM Journal on Control and Optimization
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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.