Abstract
In this paper, we present a modified two-step Levenberg–Marquardt (LM) method with the nonmonotone trust region technique for solving nonlinear equations. In each iteration, not only an LM step is computed, but also an approximate LM step that uses the previously calculated Jacobian. We establish a new adaptive LM parameter and under the local error bound condition the global and cubic convergence of the new method is proved. Numerical results indicate the promising behavior of the suggested algorithm.
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Amini, K., Rostami, F., Caristi, G.: An efficient Levenberg–Marquardt method with a new LM parameter for systems of nonlinear equations. Optimization 67(5), 637–650 (2018)
Amini, K., Rostami, F.: A modified two steps Levenberg–Marquardt method for nonlinear equations. J. Comput. Appl. Math. 288, 341–350 (2015)
Ahookhosh, M., Amini, K.: A nonmonotone trust region method with adaptive radius for unconstrained optimization. Comput. Math. Appl. 60, 411–422 (2010)
Ahookhosh, M., Amini, K.: An efficient nonmonotone trust-region method for unconstrained optimization. Numer. Algorithms 59, 523–540 (2012)
Amini, K., Rostami, F.: Three-steps modified Levenberg–Marquardt method with a new line search for systems of nonlinear equations. J. Comput. Appl. Math. 300, 30–42 (2016)
Behling, R., Iusem, A.: The effect of calmness on the solution set of systems of nonlinear equations. Math. Program. 137, 155–165 (2013)
Broyden, C.G.: Quasi-Newton methods and their applications to function minimization. Math. Comput. 21, 368–381 (1967)
Conn, A.R., Gould, N.I.M., Toint, P.L.: Trust region methods. SIAM, Philadelphia, PA (2000)
Deng, N.Y., Xiso, Y., Zhou, F.J.: Nonmonotone trust region algorithm. J. Optim. Theory Appl. 76, 259–285 (1993)
Fan, J.: A modified Levenberg–Marquardt algorithm for singular system of nonlinear equations. J. Comput. Appl. Math. 21, 625–636 (2003)
Fan, J., Yuan, Y.X.: On the quadratic convergence of the Levenberg–Marquardt method without nonsingularity assumption. Computing. 74, 23–39 (2005)
Fan, J.: The modified Levenberg–Marquardt method for nonlinear equations with cubic convergence. Math. Comput. 81, 447–466 (2012)
Fan, J.: Accelerating the modified Levenberg–Marquardt method for nonlinear equations. Math. Comput. 83, 1173–1187 (2014)
Grippo, L., Lampariello, F., Lucidi, S.: A nonmonotone line search technique for Newton’s method. SIAM J. Numer. Anal. 23, 707–716 (1986)
Grippo, L., Lampariello, F., Lucidi, S.: A truncated Newton method with nonmonotone line search for unconstrained optimization. J. Optim. Theory Appl. 69, 401–419 (1989)
Kelley, C.T.: Solving nonlinear equations with Newton’s method. SIAM, Philadelphia (2003)
Levenberg, K.: A method for the solution of certain nonlinear problems in least squares. Quart. Appl. Math. 2, 164–168 (1944)
Marquardt, D.W.: An algorithm for least-squares estimation of nonlinear parameters. J. Soc. Ind. Appl. Math. 11, 431–441 (1963)
Moré, J.J., Garbow, B.S., Hillstrom, K.E.: Testing unconstrained optimization software. ACM Trans. Math. Softw. (TOMS) 7, 17–41 (1981)
Powell, M.J.D.: Convergence properties of a class of minimization algorithms. In: Nonlinear programming, pp. 1–27. Academic Press (1975)
Schnabel, R.B., Frank, P.D.: Tensor methods for nonlinear equations. SIAM J. Numer. Anal. 21, 815–843 (1984)
Stewart, G.W., Sun, J.G.: Matrix perturbation theory. Computer science and scientific computing, Academic Press, Boston, MA (1990)
Toint, P.L.: Non-monotone trust region algorithm for nonlinear optimization subject to convex constraints. Math. Program. 77, 69–94 (1997)
Toint, P.L.: An assessment of non-monotone line search techniques for unconstrained optimization. SIAM J. Sci. Comput. 17, 725–739 (1996)
Toint, P.L.: Nonlinear step size control, trust regions and regularization for unconstrained optimization. Optim. Methods Softw. 28, 82–95 (2013)
Yamashita, N., Fukushima, M.: On the rate of convergence of the Levenberg–Marquardt method. Computing 15, 237–249 (2001)
Zhou, W.: On the convergence of the modified Levenberg–Marquardt method with a nonmonotone second order Armijo type line search. J. Comput. Appl. Math. 239, 152–161 (2013)
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Rezaeiparsa, Z., Ashrafi, A. A new adaptive Levenberg–Marquardt parameter with a nonmonotone and trust region strategies for the system of nonlinear equations. Math Sci (2023). https://doi.org/10.1007/s40096-023-00515-2
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DOI: https://doi.org/10.1007/s40096-023-00515-2