An efficient line search trust-region for systems of nonlinear equations
- Department of Mathematics, Payame Noor University, Tehran, IR
Published in Issue 2020-06-28
How to Cite
Rahpeymaii, F. (2020). An efficient line search trust-region for systems of nonlinear equations. Mathematical Sciences, 14(3 (September 2020). https://doi.org/10.1007/s40096-020-00339-4
Abstract
Abstract An improved derivative-free trust-region method to solve systems of nonlinear equations in several variables is presented, combined with the Wolfe conditions to update the trust-region radius. We believe that producing step-sizes by the Wolfe conditions can control the trust-region radius. The new algorithm for which strong global convergence properties are proved is robust and efficient enough to solve systems of nonlinear equations.Keywords
- Nonlinear equations,
- Derivative-free optimization,
- Trust-region method,
- Line search,
- Wolfe conditions,
- Global convergence
References
- Ahookhosh et al. (2015) A globally convergent trust-region method for large-scale symmetric nonlinear systems (pp. 830-855)
- Ahookhosh et al. (2013) An effective trust-region-based approach for symmetric nonlinear systems 90(3) (pp. 671-690)
- Amini et al. (2016) A nonmonotone trust-region-approach with nonmonotone adaptive radius for solving nonlinear systems 6(1) (pp. 101-121)
- Amini et al. (2016) A line search trust-region algorithm with nonmonotone adaptive radius for a system of nonlinear equations 14(2) (pp. 132-152)
- Bouaricha and Schnabel (1998) Tensor methods for large sparse systems of nonlinear equations (pp. 377-400)
- Broyden (1971) The convergence of an algorithm for solving sparse nonlinear systems 25(114) (pp. 285-294)
- Buhmiler et al. (2010) Practical quasi-Newton algorithms for singular nonlinear systems (pp. 481-502)
- Conn et al. (2000) SIAM
- Dedieu and Shub (2000) Newton’s method for overdetermined systems of equations 69(231) (pp. 1099-1115)
- Dennis (1971) On the convergence of Broyden’s method for nonlinear systems of equations 25(115) (pp. 559-567)
- Dolan and Moré (2002) Benchmarking optimization software with performance profiles (pp. 201-213)
- Esmaeili and Kimiaei (2014) A new adaptive trust-region method for system of nonlinear equations 38(11–12) (pp. 3003-3015)
- Esmaeili and Kimiaei (2015) An efficient adaptive trust-region method for systems of nonlinear equations (pp. 151-166)
- Fan (2005) Convergence rate of the trust region method for nonlinear equations under local error bound condition (pp. 215-227)
- Fan (2011) An improved trust region algorithm for nonlinear equations (pp. 59-70)
- Fasano et al. (2006) truncated nonmonotone Gauss–Newton method for large-scale nonlinear least-squares problems 34(3) (pp. 343-358)
- Gertz (2004) A quasi-Newton trust-region method (pp. 447-470)
- Gertz (1999) University of California
- Gill and Murray (1978) Algorithms for the solution of the nonlinear least-squares problem 15(5) (pp. 977-992)
- Gill, P.E., Wright, M.H.: Department of Mathematics University of California San Diego. Course Notes for Numerical Nonlinear Optimization (2001)
- Griewank (1986) The global convergence of Broyden-like methods with a suitable line search (pp. 75-92)
- Grippo and Sciandrone (2007) Nonmonotone derivative-free methods for nonlinear equations (pp. 297-328)
- Gu et al. (2003) Descent directions of quasi-Newton methods for symmetric nonlinear equations 40(5) (pp. 1763-1774)
- Kimiaei (2017) A new class of nonmonotone adaptive trust-region methods for nonlinear equations with box constraints 54(3) (pp. 769-812)
- Kimiaei and Rahpeymaii (2019) A new nonmonotone line-search trust-region approach for nonlinear systems (pp. 199-232)
- Kimiaei (2018) Nonmonotone self-adaptive Levenberg–Marquardt approach for solving systems of nonlinear equations 39(21) (pp. 47-66)
- Kimiaei and Esmaeili (2016) A trust-region approach with novel filter adaptive radius for system of nonlinear equations 73(4) (pp. 999-1016)
- Levenberg (1944) A method for the solution of certain non-linear problems in least squares (pp. 164-166)
- Li and Li (2011) A class of derivative-free methods for large-scale nonlinear monotone equations 31(4) (pp. 1-11)
- Li and Fukushima (1999) A global and superlinear convergent Gauss–Newton-based BFGS method for symmetric nonlinear equations (pp. 152-172)
- Marquardt (1963) An algorithm for least-squares estimation of nonlinear parameters (pp. 431-441)
- Martinez (1990) A family of quasi-Newton methods for nonlinear equations with direct secant updates of matrix factorizations 27(4) (pp. 1034-1049)
- Moré et al. (1981) Testing unconstrained optimization software (pp. 17-41)
- Nocedal and Wright (2006) Springer
- Nocedal, J., Yuan, Y.X.: Combining trust-region and line-search techniques, Optimization Technology Center mar OTC 98/04 (1998)
- Ortega and Rheinboldt (1970) Academic Press
- Powell et al. (1970) A new algorithm for unconstrained optimization Academic Press
- Powell et al. (1975) Convergence properties of a class of minimization algorithms (pp. 1-27) Academic Press
- Rahpeymaii et al. (2016) A limited memory quasi-Newton trust-region method for box constrained optimization (pp. 105-118)
- Schnabel and Frank (1984) Tensor methods for nonlinear equations 21(5) (pp. 815-843)
- Thomas (1975) Cornell University
- Toint (1986) Numerical solution of large sets of algebraic nonlinear equations 46(173) (pp. 175-189)
- Toint and Duff (1982) Towards an efficient sparsity exploiting Newton method for minimization (pp. 57-87) New York
- Tong and Qi (2004) On the convergence of a trust-region method for olving constrained nonlinear equations with degenerate solutions 123(1) (pp. 187-211)
- Yamashita and Fukushima (2001) On the rate of convergence of the Levenberg–Marquardt method (pp. 239-249)
- Yuan et al. (2011) A BFGS trust-region method for nonlinear equations 92(4) (pp. 317-333)
- Yuan (2009) Subspace methods for large scale nonlinear equations and nonlinear least squares (pp. 207-218)
- Yuan (1998) Trust region algorithm for nonlinear equations (pp. 7-21)
- Yuan (2011) Recent advances in numerical methods for nonlinear equations and nonlinear least squares 1(1) (pp. 15-34)
- Zhang and Wang (2003) A new trust region method for nonlinear equations (pp. 283-298)
10.1007/s40096-020-00339-4