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Erschienen in: 4OR 2/2016

27.01.2016 | Research paper

A line search trust-region algorithm with nonmonotone adaptive radius for a system of nonlinear equations

verfasst von: Keyvan Amini, Mushtak A. K. Shiker, Morteza Kimiaei

Erschienen in: 4OR | Ausgabe 2/2016

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Abstract

In this paper, a trust-region procedure is proposed for the solution of nonlinear equations. The proposed approach takes advantages of an effective adaptive trust-region radius and a nonmonotone strategy by combining both of them appropriately. It is believed that selecting an appropriate adaptive radius based on a suitable nonmonotone strategy can improve the efficiency and robustness of the trust-region frameworks as well as decrease the computational cost of the algorithm by decreasing the required number subproblems that must be solved. The global convergence and the local Q-quadratic convergence rate of the proposed approach are proved. Preliminary numerical results of the proposed algorithm are also reported which indicate the promising behavior of the new procedure for solving the nonlinear system.

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Literatur
Zurück zum Zitat Ahookhosh M, Amini K (2010) A nonmonotone trust-region method with adaptive radius for unconstrained optimization. Comput Math Appl 60:411–422CrossRef Ahookhosh M, Amini K (2010) A nonmonotone trust-region method with adaptive radius for unconstrained optimization. Comput Math Appl 60:411–422CrossRef
Zurück zum Zitat Ahookhosh M, Amini K, Peyghami MR (2012) A nonmonotone trust-region line search method for large-scale unconstrained optimization. Appl Math Model 36:478–487CrossRef Ahookhosh M, Amini K, Peyghami MR (2012) A nonmonotone trust-region line search method for large-scale unconstrained optimization. Appl Math Model 36:478–487CrossRef
Zurück zum Zitat Bellavia S, Macconi M, Morini B (2004) STRSCNE: a scaled trust-region solver for constrained nonlinear equations. Comput Optim Appl 28:31–50CrossRef Bellavia S, Macconi M, Morini B (2004) STRSCNE: a scaled trust-region solver for constrained nonlinear equations. Comput Optim Appl 28:31–50CrossRef
Zurück zum Zitat Conn AR, Gould NIM, Toint PhL (2000) Trust-region methods. Society for Industrial and Applied Mathematics SIAM, PhiladelphiaCrossRef Conn AR, Gould NIM, Toint PhL (2000) Trust-region methods. Society for Industrial and Applied Mathematics SIAM, PhiladelphiaCrossRef
Zurück zum Zitat Dolan ED, Moré JJ (2002) Benchmarking optimization software with performance profiles. Math Program 91:201–213CrossRef Dolan ED, Moré JJ (2002) Benchmarking optimization software with performance profiles. Math Program 91:201–213CrossRef
Zurück zum Zitat Esmaeili H, Kimiaei M (2014) A new adaptive trust-region method for system of nonlinear equations. Appl Math Model 38:3003–3015CrossRef Esmaeili H, Kimiaei M (2014) A new adaptive trust-region method for system of nonlinear equations. Appl Math Model 38:3003–3015CrossRef
Zurück zum Zitat Esmaeili H, Kimiaei M (2015) An efficient adaptive trust-region method for systems of nonlinear equations. Int J Comput Math 92(1):151–166CrossRef Esmaeili H, Kimiaei M (2015) An efficient adaptive trust-region method for systems of nonlinear equations. Int J Comput Math 92(1):151–166CrossRef
Zurück zum Zitat Fan JY (2005) Convergence rate of the trust region method for nonlinear equations under local error bound condition. Comput Optim Appl 34:215–227CrossRef Fan JY (2005) Convergence rate of the trust region method for nonlinear equations under local error bound condition. Comput Optim Appl 34:215–227CrossRef
Zurück zum Zitat Fan JY(2011)An improved trust region algorithmfor nonlinear equations.ComputOptimAppl 48(1):59–70 Fan JY(2011)An improved trust region algorithmfor nonlinear equations.ComputOptimAppl 48(1):59–70
Zurück zum Zitat Fan JY, Pan JY (2010) A modified trust region algorithm for nonlinear equations with new updating rule of trust region radius. Int J Comput Math 87(14):3186–3195CrossRef Fan JY, Pan JY (2010) A modified trust region algorithm for nonlinear equations with new updating rule of trust region radius. Int J Comput Math 87(14):3186–3195CrossRef
Zurück zum Zitat Fasano G, Lampariello F, Sciandrone M (2006) A truncated nonmonotone Gauss–Newton method for large-scale nonlinear least-squares problems. Comput Optim Appl 34(3):343–358CrossRef Fasano G, Lampariello F, Sciandrone M (2006) A truncated nonmonotone Gauss–Newton method for large-scale nonlinear least-squares problems. Comput Optim Appl 34(3):343–358CrossRef
Zurück zum Zitat Fischer A, Shukla PK, Wang M (2010) On the inexactness level of robust Levenberg–Marquardt methods. Optimization 59(2):273–287CrossRef Fischer A, Shukla PK, Wang M (2010) On the inexactness level of robust Levenberg–Marquardt methods. Optimization 59(2):273–287CrossRef
Zurück zum Zitat Gertz EM (1999) Combination trust-region line-search methods for unconstrained optimization. University of California San Diego, San Diego Gertz EM (1999) Combination trust-region line-search methods for unconstrained optimization. University of California San Diego, San Diego
Zurück zum Zitat Grippo L, Lampariello F, Lucidi S (1986) A nonmonotone line search technique for Newton’s method. SIAM J Numer Anal 23:707–716CrossRef Grippo L, Lampariello F, Lucidi S (1986) A nonmonotone line search technique for Newton’s method. SIAM J Numer Anal 23:707–716CrossRef
Zurück zum Zitat Grippo L, Lampariello F, Lucidi S (1989) A truncated Newton method with nonmonotone linesearch for unconstrained optimization. J Optim Theory Appl 60(3):401–419CrossRef Grippo L, Lampariello F, Lucidi S (1989) A truncated Newton method with nonmonotone linesearch for unconstrained optimization. J Optim Theory Appl 60(3):401–419CrossRef
Zurück zum Zitat Grippo L, Lampariello F, Lucidi S (1991) A class of nonmonotone stabilization method in unconstrained optimization. Numer Math 59:779–805CrossRef Grippo L, Lampariello F, Lucidi S (1991) A class of nonmonotone stabilization method in unconstrained optimization. Numer Math 59:779–805CrossRef
Zurück zum Zitat Grippo L, Sciandrone M (2007) Nonmonotone derivative-free methods for nonlinear equations. Comput Optim Appl 37:297–328CrossRef Grippo L, Sciandrone M (2007) Nonmonotone derivative-free methods for nonlinear equations. Comput Optim Appl 37:297–328CrossRef
Zurück zum Zitat La Cruz W, Raydan M (2003) Nonmonotone spectral methods for large-scale nonlinear systems. Optim Methods Softw 18(5):583–599CrossRef La Cruz W, Raydan M (2003) Nonmonotone spectral methods for large-scale nonlinear systems. Optim Methods Softw 18(5):583–599CrossRef
Zurück zum Zitat La Cruz W, Venezuela C, Martínez JM, Raydan M (2004) Spectral residual method without gradient information for solving large-scale nonlinear systems of equations: theory and experiments. In: Technical report RT-04-08, July 2004 La Cruz W, Venezuela C, Martínez JM, Raydan M (2004) Spectral residual method without gradient information for solving large-scale nonlinear systems of equations: theory and experiments. In: Technical report RT-04-08, July 2004
Zurück zum Zitat Li DH, Fukushima M (2000a) A derivative-free line search and global convergence of Broyden-like method for nonlinear equations. Optim Methods Softw 13:181–201 Li DH, Fukushima M (2000a) A derivative-free line search and global convergence of Broyden-like method for nonlinear equations. Optim Methods Softw 13:181–201
Zurück zum Zitat Li DH, Fukushima M (2000b) A globally and superlinearly convergent Gauss–Newton-Based BFGS method for symmetric nonlinear equations. SIAM J Numer Anal 37(1):152–172 Li DH, Fukushima M (2000b) A globally and superlinearly convergent Gauss–Newton-Based BFGS method for symmetric nonlinear equations. SIAM J Numer Anal 37(1):152–172
Zurück zum Zitat Lukšan L, Vlček J (1999) Sparse and partially separable test problems for unconstrained and equality constrained optimization. In: Technical report, no 767 Lukšan L, Vlček J (1999) Sparse and partially separable test problems for unconstrained and equality constrained optimization. In: Technical report, no 767
Zurück zum Zitat Nocedal J, Yuan YX (1998) Combining Trust-region and line-search techniques. Optimization Technology Center mar OTC 98(04) 1998 Nocedal J, Yuan YX (1998) Combining Trust-region and line-search techniques. Optimization Technology Center mar OTC 98(04) 1998
Zurück zum Zitat Nocedal J, Wright SJ (2006) Numerical optimization. Springer, New York Nocedal J, Wright SJ (2006) Numerical optimization. Springer, New York
Zurück zum Zitat Sartenaer A (1997) Automatic determination of an initial trust region in nonlinear programming. SIAM J Sci Comput 18(6):1788–1803CrossRef Sartenaer A (1997) Automatic determination of an initial trust region in nonlinear programming. SIAM J Sci Comput 18(6):1788–1803CrossRef
Zurück zum Zitat Toint Ph L (1982) Towards an efficient sparsity exploiting Newton method for minimization. In: Sparse matrices and their uses. Academic Press, New York 1982 I. S. Duff 57–87 Toint Ph L (1982) Towards an efficient sparsity exploiting Newton method for minimization. In: Sparse matrices and their uses. Academic Press, New York 1982 I. S. Duff 57–87
Zurück zum Zitat Toint PhL (1986) Numerical solution of large sets of algebraic nonlinear equations. Math. Comput. 46(173):175–189CrossRef Toint PhL (1986) Numerical solution of large sets of algebraic nonlinear equations. Math. Comput. 46(173):175–189CrossRef
Zurück zum Zitat Yamashita N, Fukushima M (2001) On the rate of convergence of the Levenberg–Marquardt method. Computing 15:239–249 Yamashita N, Fukushima M (2001) On the rate of convergence of the Levenberg–Marquardt method. Computing 15:239–249
Zurück zum Zitat Yuan G, Lu S, Wei Z (2011) A new trust-region method with line search for solving symmetric nonlinear equations. Int J Comput Math 88(10):2109–2123CrossRef Yuan G, Lu S, Wei Z (2011) A new trust-region method with line search for solving symmetric nonlinear equations. Int J Comput Math 88(10):2109–2123CrossRef
Zurück zum Zitat Yuan Y (1998) Trust region algorithm for nonlinear equations. Information 1:7–21 Yuan Y (1998) Trust region algorithm for nonlinear equations. Information 1:7–21
Zurück zum Zitat Zhang HC, Hager WW (2004) A nonmonotone line search technique for unconstrained optimization. SIAM J Optim 14(4):1043–1056CrossRef Zhang HC, Hager WW (2004) A nonmonotone line search technique for unconstrained optimization. SIAM J Optim 14(4):1043–1056CrossRef
Zurück zum Zitat Zhang J, Wang Y (2003) A new trust region method for nonlinear equations. Math Methods Oper Res 58:283–298CrossRef Zhang J, Wang Y (2003) A new trust region method for nonlinear equations. Math Methods Oper Res 58:283–298CrossRef
Zurück zum Zitat Zhang XS, Zhang JL, Liao LZ (2002) An adaptive trust region method and its convergence. Sci China 45:620–631 Zhang XS, Zhang JL, Liao LZ (2002) An adaptive trust region method and its convergence. Sci China 45:620–631
Metadaten
Titel
A line search trust-region algorithm with nonmonotone adaptive radius for a system of nonlinear equations
verfasst von
Keyvan Amini
Mushtak A. K. Shiker
Morteza Kimiaei
Publikationsdatum
27.01.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
4OR / Ausgabe 2/2016
Print ISSN: 1619-4500
Elektronische ISSN: 1614-2411
DOI
https://doi.org/10.1007/s10288-016-0305-3

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