×

A new three-term conjugate gradient method with descent direction for unconstrained optimization. (English) Zbl 1488.49059

Summary: In this paper, we propose a three-term PRP-type conjugate gradient method which always satisfies the sufficient descent condition independently of line searches employed. An important property of our method is that its direction is closest to the direction of the Newton method or satisfies conjugacy condition as the iterations evolve. In addition, under mild condition, we prove global convergence properties of the proposed method. Numerical comparison illustrates that our proposed method is efficient for solving the optimization problems.

MSC:

49M37 Numerical methods based on nonlinear programming
65K05 Numerical mathematical programming methods
90C53 Methods of quasi-Newton type

Software:

CUTE
Full Text: DOI

References:

[1] N. Andrei. On three-term conjugate gradient algorithms for unconstrained op- timization. Applied Mathematics and Computation, 219(11):6316-6327, 2013. http://dx.doi.org/10.1016/j.amc.2012.11.097. · Zbl 1274.90372 · doi:10.1016/j.amc.2012.11.097
[2] N. Andrei. A simple three-term conjugate gradient algorithm for unconstrained optimization. Journal of Computational and Applied Mathematics, 241:19-29, 2013. http://dx.doi.org/10.1016/j.cam.2012.10.002. · Zbl 1258.65056 · doi:10.1016/j.cam.2012.10.002
[3] S. Babaie-Kafaki and R. Ghanbari. A descent family of Dai-Liao conjugate gradient methods. Optimization Methods and Software, 29(3):583-591, 2014. http://dx.doi.org/10.1080/10556788.2013.833199. · Zbl 1285.90063
[4] S. Babaie-Kafaki and R. Ghanbari. A hybridization of the Polak-Ribìre- Polyak and Fletcher-Reeves conjugate gradient methods. Numerical Algorithms, 68(3):481-495, 2014. http://dx.doi.org/10.1007/s11075-014-9856-6. · Zbl 1311.65066 · doi:10.1007/s11075-014-9856-6
[5] S. Babaie-Kafaki and N. Mahdavi-Amiri. Two modified hybrid conjugate gra- dient methods based on a hybrid secant equation. Mathematical Modelling and Analysis, 18(1):32-52, 2013. http://dx.doi.org/10.3846/13926292.2013.756832. · Zbl 1264.49034
[6] I. Bongartz, A.R. Conn, N. Gould and Ph.L. Toint. CUTE: Constrained and un- constrained testing environment. ACM Transactions on Mathematical Software, 21(1):123-160, 1995. http://dx.doi.org/10.1145/200979.201043. · Zbl 0886.65058 · doi:10.1145/200979.201043
[7] W. Cheng. A two-term PRP-based descent method. Numeri- cal Functional Analysis and Optimization, 28(11-12):1217-1230, 2007. http://dx.doi.org/10.1080/01630560701749524. · Zbl 1138.90028
[8] Y.H. Dai and C.X. Kou. A nonlinear conjugate gradient algorithm with an opti- mal property and an improved Wolfe line search. SIAM Journal on Optimization, 23(1):296-320, 2013. http://dx.doi.org/10.1137/100813026. · Zbl 1266.49065 · doi:10.1137/100813026
[9] Y.H. Dai and L.Z. Liao. New conjugacy conditions and related nonlinear con- jugate gradient methods. Applied Mathematics and Optimization, 43(1):87-101, 2001. http://dx.doi.org/10.1007/s002450010019. · Zbl 0973.65050 · doi:10.1007/s002450010019
[10] D.E. Dolan and J.J. Moré. Benchmarking optimization software with performance profiles. Mathematical Programming, 91(2):201-213, 2002. http://dx.doi.org/10.1007/s101070100263. · Zbl 1049.90004 · doi:10.1007/s101070100263
[11] X.L. Dong, H. Liu, Y.L. Xu and X.M. Yang. Some nonlinear conjugate gradient methods with sufficient descent condition and global convergence. Optimization Letters, 9(7):1421-1432, 2014. http://dx.doi.org/10.1007/s11590-014-0836-5. · Zbl 1332.90344 · doi:10.1007/s11590-014-0836-5
[12] X.L. Dong, H.W. Liu and Y.B. He. A self-adjusting conjugate gra- dient method with sufficient descent condition and conjugacy condition. Journal of Optimization Theory and Applications, 165(1):225-241, 2014. http://dx.doi.org/10.1007/s10957-014-0601-z. · Zbl 1322.90094 · doi:10.1007/s10957-014-0601-z
[13] X.L. Dong, H.W. Liu and Y.B. He. New version of the three-term conjugate gradient method based on spectral scaling conjugacy condition that generates descent search direction. Applied Mathematics and Computation, 269:606-617, 2015. http://dx.doi.org/10.1016/j.amc.2015.07.067. · Zbl 1410.90195 · doi:10.1016/j.amc.2015.07.067
[14] X.L. Dong, H.W. Liu, Y.B. He and X.M. Yang. A modified Hestenes-Stiefel conjugate gradient method with sufficient descent condition and conjugacy con- dition. Journal of Computational and Applied Mathematics, 281:239-249, 2015. http://dx.doi.org/10.1016/j.cam.2014.11.058. · Zbl 1309.65074 · doi:10.1016/j.cam.2014.11.058
[15] R. Fletcher and C.M. Reeves. Function minimization by con- jugate gradients. The Computer Journal, 7(2):149-154, 1964. http://dx.doi.org/10.1093/comjnl/7.2.149. · Zbl 0132.11701 · doi:10.1093/comjnl/7.2.149
[16] J.Ch. Gilbert and J. Nocedal. Global convergence properties of conjugate gradi- ent methods for optimization. SIAM Journal on Optimization, 2(1):21-42, 1992. http://dx.doi.org/10.1137/0802003. · Zbl 0767.90082 · doi:10.1137/0802003
[17] W.W. Hager and H. Zhang. A new conjugate gradient method with guaranteed descent and an efficient line search. SIAM Journal on Optimization, 16(1):170-192, 2005. http://dx.doi.org/10.1137/030601880. · Zbl 1093.90085 · doi:10.1137/030601880
[18] W.W. Hager and H. Zhang. A survey of nonlinear conjugate gradient methods. Pacific journal of Optimization, 2(1):35-58, 2006. · Zbl 1117.90048
[19] M.R. Hestenes and E. Stiefel. Methods of conjugate gradients for solving linear systems. Journal of Research of the National Bureau of Standards, 49(6):409-436, 1952. · Zbl 0048.09901 · doi:10.6028/jres.049.044
[20] I.E. Livieris and P. Pintelas. A descent Dai-Liao conjugate gradient method based on a modified secant equation and its global convergence. ISRN Computational Mathematics, 2012, 2012. http://dx.doi.org/10.5402/2012/435495. · Zbl 1245.65067 · doi:10.5402/2012/435495
[21] I.E. Livieris and P. Pintelas. A new class of spectral conjugate gradient methods based on a modified secant equation for unconstrained optimiza- tion. Journal of Computational and Applied Mathematics, 239:396-405, 2013. http://dx.doi.org/10.1016/j.cam.2012.09.007. · Zbl 1258.65058 · doi:10.1016/j.cam.2012.09.007
[22] I.E. Livieris and P. Pintelas. A modified Perry conjugate gradient method and its global convergence. Optimization Letters, 9(5):999-1015, 2015. http://dx.doi.org/10.1007/s11590-014-0820-0. · Zbl 1328.90141 · doi:10.1007/s11590-014-0820-0
[23] Y. Narushima, H. Yabe and J.A. Ford. A three-term conjugate gradient method with sufficient descent property for unconstrained optimization. SIAM Journal on Optimization, 21(1):212-230, 2011. http://dx.doi.org/10.1137/080743573. · Zbl 1250.90087 · doi:10.1137/080743573
[24] B.T. Polyak. The conjugate gradient method in extremal problems. USSR Computational Mathematics and Mathematical Physics, 9(4):94-112, 1969. http://dx.doi.org/10.1016/0041-5553(69)90035-4. · Zbl 0229.49023 · doi:10.1016/0041-5553(69)90035-4
[25] D.F. Shanno. On the convergence of a new conjugate gradient algo- rithm. SIAM Journal on Numerical Analysis, 15(6):1247-1257, 1978. http://dx.doi.org/10.1137/0715085. · Zbl 0408.90071 · doi:10.1137/0715085
[26] Sohu.com.: Numerical results on NPRP/TMPRP/HZ. Available from Internet: http://shuxueyou.blog.sohu.com/310274007.html.
[27] Ph. Wolfe. Convergence conditions for ascent methods. SIAM review, 11(2):226-235, 1969. http://dx.doi.org/10.1137/1011036. · Zbl 0177.20603 · doi:10.1137/1011036
[28] G. Yu, L. Guan and W. Chen. Spectral conjugate gradient meth- ods with sufficient descent property for large-scale unconstrained op- timization. Optimization Methods and Software, 23(2):275-293, 2008. http://dx.doi.org/10.1080/10556780701661344. · Zbl 1279.90166
[29] L. Zhang, W. Zhou and D.H. Li. A descent modified Polak-Ribìere-Polyak con- jugate gradient method and its global convergence. IMA Journal of Numerical Analysis, 26(4):629-640, 2006. http://dx.doi.org/10.1093/imanum/drl016. · Zbl 1106.65056 · doi:10.1093/imanum/drl016
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.