A trust-region method by active-set strategy for general nonlinear optimization

Authors:
Ying Ji;Ke-Cun Zhang;Shao-Jian Qu;Ying Zhou
Affiliations:
Faculty of Science, Xi'an Jiaotong University, Xi'an 710049, PR China;Faculty of Science, Xi'an Jiaotong University, Xi'an 710049, PR China;Faculty of Science, Xi'an Jiaotong University, Xi'an 710049, PR China;Faculty of Science, Xi'an Jiaotong University, Xi'an 710049, PR China
Venue:
Computers & Mathematics with Applications
Year:
2007

Citing 5
Cited 2

Practical methods of optimization; (2nd ed.)

Practical methods of optimization; (2nd ed.)
A trust region algorithm for equality constrained optimization

Mathematical Programming: Series A and B
New minimax algorithm

Journal of Optimization Theory and Applications
A Modified SQP Method and Its Global Convergence

Journal of Global Optimization
A Branch and Bound Method via d.c. Optimization Algorithms andEllipsoidal Technique for Box Constrained Nonconvex Quadratic Problems

Journal of Global Optimization

A new hybrid method for nonlinear complementarity problems

Computational Optimization and Applications
Hybrid PID-fuzzy control scheme for managing energy resources in buildings

Applied Soft Computing

Quantified Score

Hi-index	0.09

Visualization

Abstract

The paper explores a trust-region active-set algorithm for general nonlinear optimization with nonlinear equality and inequality constraints. In this algorithm, an active-set strategy is used together with trust-region methods to compute the trial step. L"1 penalty functions are employed to obtain the global convergence. The global convergence of this algorithm is proved under standard conditions. The numerical tests show the efficiency of the proposed algorithm.