Abstract
In this paper, we combine trust region technique with line search technique to develop an iterative method for solving semismooth equations. At each iteration, a trust region subproblem is solved. The solution of the trust region subproblem provides a descent direction for the norm of a smoothing function. By using a backtracking line search, a steplength is determined. The proposed method shares advantages of trust region methods and line search methods. Under appropriate conditions, the proposed method is proved to be globally and superlinearly convergent. In particular, we show that after finitely many iterations, the unit step is always accepted and the method reduces to a smoothing Newton method.
Original language | English |
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Pages (from-to) | 1-10 |
Number of pages | 10 |
Journal | Journal of Computational and Applied Mathematics |
Volume | 146 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 Sept 2002 |
Keywords
- Line search
- Semismooth equation
- Smoothing function
- Trust region method
ASJC Scopus subject areas
- Computational Mathematics
- Applied Mathematics