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A New Hybrid Conjugate Gradient Method Based on Eigenvalue Analysis for Unconstrained Optimization Problems | ||
Control and Optimization in Applied Mathematics | ||
مقاله 2، دوره 3، شماره 1، مهر 2018، صفحه 27-43 اصل مقاله (532.11 K) | ||
نوع مقاله: Research Article | ||
شناسه دیجیتال (DOI): 10.30473/coam.2019.44564.1108 | ||
نویسندگان | ||
Farzad Rahpeymaii* 1؛ majid rostami2 | ||
1Department of Mathematics, Payame Noor University, PO BOX 19395-3697, Tehran, Iran | ||
2Young Researchers and Elite Club‎, ‎Hamedan Branch‎, ‎Islamic Azad University‎, ‎Hamedan‎, ‎Iran | ||
چکیده | ||
In this paper, two extended three-term conjugate gradient methods based on the Liu-Storey ({\tt LS}) conjugate gradient method are presented to solve unconstrained optimization problems. A remarkable property of the proposed methods is that the search direction always satisfies the sufficient descent condition independent of line search method, based on eigenvalue analysis. The global convergence of proposed algorithms is established under suitable conditions. Preliminary numerical results show that the proposed methods are efficient and robust to solve the unconstrained optimization problems. | ||
کلیدواژهها | ||
Unconstrained optimization؛ Conjugate gradient methods؛ Eigenvalue analysis؛ Global convergence؛ Numerical comparisons | ||
عنوان مقاله [English] | ||
یک روش گرادیان مزدوج ترکیبی جدید بر پایه آنالیز مقادیر ویژه برای مسائل بهینهسازی نامقید | ||
نویسندگان [English] | ||
فرزاد راهپیمایی1؛ مجید رستمی2 | ||
چکیده [English] | ||
در این مقاله، دو روش گرادیان مزدوج سهجملهای تعمیمیافته بر پایه روش گرادیان مزدوج لیو-استوری برای حل مسائل بهینهسازی نامقید ارائه شده است. ویژگی مهم و اصلی روشهای جدید، تولید جهتهای جستجوی کاهشی بر پایه آنالیز مقادیر ویژه و مستقل از نوع جستجوی خطی است. همگرایی سراسری الگوریتمهای جدید ارائه شده تحت برخی فرضهای مناسب اثبات شده است. نتایج عددی نشان میدهند که روشهای پیشنهادی برای حل مسائل بهینهسازی نامقید کارا و قوی هستند. | ||
کلیدواژهها [English] | ||
بهینهسازی نامقید, روشهای گرادیان مزدوج, آنالیز مقادیر ویژه, همگرایی سراسری, مقایسههای عددی | ||
مراجع | ||
bibitem{AhoAP} Ahookhosh M., Amini K., Peyghami M.R. (2012). ``A nonmonotone trust--region line search method for large-scale unconstrained optimization", Applied Mathematical Modelling, 36(1), 478--487.
bibitem{A15} Andrei N. (2015). ``A new three--term conjugate gradient algorithm for unconstrained optimization", Applied Mathematical Modelling, 68, 305--321. bibitem{B72} Beale E.M.L. (1972). ``A derivative of conjugate gradients, in: Lootsma F A, eds. Numerical methods for nonlinear optimization", London, Academic Press, 39--43. bibitem{CUTEST} Conn A. R., Gould N. I. M., Toint Ph. L. (1995). ``CUTE: constrained and unconstrained testing environment", ACM T. Math. Software, 21, 123--160. bibitem{DY99} Dai Y., Yuan Y. (1999). ``A nonlinear conjugate gradient method with a strong global convergence property", SIAM Journal on Optimization, 10(1), 177--182. bibitem{D19} Djordjevic S.S. (2019). ``New hybrid conjugate gradient method as a convex combination of LS and FR methods", Acta Mathematica Scientia, 39B(1), 214--228. bibitem{DM} Dolan E.D., Mor'{e} J. (2012). ``Benchmarking optimization software with performance profiles", Mathematical Programming Ser A, 91(2), 201--213. bibitem{EM} Edelman A., Mith T.S. (1996). ``On conjugate gradient--like methods for eigen--like problems", BIT Numerical Mathematics, 36(1), 1--16. bibitem{EK14} Esmaeili H., Kimiaei M. (2014). ``An improved adaptive trust--region method for unconstrained optimization", Mathematical Modelling and Analysis, 19(4), 469--490. bibitem{ERK} Esmaeili H., Rostami M., Kimiaei M. (2018). ``Extended Dai--Yuan conjugate gradient strategy for large--scale unconstrained optimization with applications to compressive sensing", Filomat, 32(6), 323--337. bibitem{F} Fletcher R. (1987). ``{em Practical methods of optimization, in: Unconstrained Optimization}", John Wiley & Sons, New York. bibitem{FR64} Fletcher R., Reeves C. (1964). ``Function minimization by conjugate gradients", Computer Journal, 72(2), 149--154. bibitem{GL01} Gill P., Leonard M.W. (2001). ``Reduced--Hessian Quasi--Newton methods for unconstrained optimization", SIAM Journal on Optimization, 12(1), 209--237. bibitem{GM72} Gill P., Murry W. (1972). ``Quasi--Newton Methods for Unconstrained Optimization", IMA Journal of Applied Mathematics, 9(1), 91--108. bibitem{GLL86} Grippo L., Lamparillo F., Lucidi S. (1986). ``A nonmonotone line search technique for Newtons method", SIAM Journal on Numerical Analysis, 23, 707--716. bibitem{HZ06} Hager W.W., Zhang H. (2006). ``A survey of nonlinear conjugate gradient methods", Pacific journal of Optimization, 2(1), 35--58. bibitem{HS} Hestenes M.R., Stiefel E.L. (1952). ``Methods of conjugate gradients for solving linear systems", Journal of Research of the National Bureau of Standards, 49, 409--436. bibitem{KGH17} Kimiaei M., Ghaderi S. (2017). ``A new restarting adaptive trust--region method for unconstrained optimization", Journal of the Operations Research Society of China, 5(4), 487--507. bibitem{KR16} Kimiaei M., Rostami M. (2016). ``Impulse noise removal based on new hybrid conjugate gradient approach", Kybernetika, 52(5), 791--823. bibitem{LCD97} Li Z.F., Chen J., Deng N.Y. (1997). ``A New Conjugate Gradient Method and Its Global Convergence Properties", Mathematical Programming, 78, 375--391. bibitem{LF11} Li M., Feng H. (2011). ``A sufficient descent LS conjugate gradient method for unconstrained optimization problems", Applied Mathematics and Computation, 218, 1577--1586. bibitem{LS91} Liu Y.L., Storey C. (1991). ``Efficient generalized conjugate gradient algorithms", part1: Journal of Optimization Theory and Applications, 69(1), 129--137. bibitem{NYF} Narushima Y., Yabe H., Ford J.A. (2011). ``A three--term conjugate gradient method with sufficient descent property for unconstrained optimization", SIAM Journal on Optimization, 21, 212--230. bibitem{NW} Nocedal J, Wright S. (2006). ``{em Numerical Optimization}", Springer, New York. bibitem{PR} Polak E., Ribi`{e}re G. (1969). ``Note sur la convergence de directions conjugu'{e}e", Rev. Francaise Informat Recherche Operationelle, 3e Ann'{e}e, 16, 35--43. bibitem{P} Polyak B.T. (1969). ``The conjugate gradient method in extreme problems", USSR Computational Mathematics and Mathematical Physics, 9, 94--112. bibitem{P84} Powell M.J.D. (1984). ``Nonconvex minimization calculations and the conjugate gradient method", in: Numerical Analysis (Dundee, 1983), Lecture Notes in Mathematics. 1066, Springer, Berlin, 122--141. bibitem{GS} Strang G. (2016). `` {em Introduction to Linear Algebra}", Springer, Fifth Edition, New York. bibitem{WZW08} Wang F., Zhang K., Wang C., Wang L. (2008). ``A variant of trust--region methods for unconstrained optimization", Applied Mathematics and Computation, 203, 297--307. bibitem{YH18} Yuan G., Hu W. (2018). ``A conjugate gradient algorithm for large--scale unconstrained optimization problems and nonlinear equations", Journal of Inequalities and Applications, 113, https://doi.org/10.1186/s13660--018--1703--1. bibitem{YLD13} Yang X., Luo Z., Dai X. (2013). ``A global convergence of LS--CD hybrid conjugate gradient method", Advances in Numerical Analysis, 517--452. bibitem{YSA} Yang X., Sarkar T. P., Arvas E. (1989). ``A survey of conjugate gradient algorithms for solution of extreme eigenproblems of a symmetric matrix", IEEE Trans. Acoust. Speech Signal Processing, 37, 1550--1556. bibitem{Z09} Zhang L. (2009). ``A new Liu--Storey type nonlinear conjugate gradient method for unconstrained optimization problems", J. Comput. Appl. Math, 225, 146--157. bibitem{ZH14} Zhang H., Hager W.W. (2014). ``A nonmonotone line search technique and its application to nuconstrained optimization", SIAM Journal on Optimization, 14( 4), 1043--1056. bibitem{ZZL} Zhang L., Zhou W., Li D.H. (2006). ``A descent modified Polak-Ribi`{e}re-Polyak conjugate gradient method and its global convergence", IMA Journal of Numerical Analysis, 26(4), 629--640. bibitem{ZZL07} Zhang L., Zhou W., Li D. (2007). ``Some descent three--term conjugate gradient methods and their global convergence", Optim Methods Software, 22(4), 697--711. bibitem{ZhSh18} Zheng X., Shi J. (2018). ``A Modified Sufficient Descent Polak–Ribiére–Polyak Type Conjugate Gradient Method for Unconstrained Optimization Problems", Algorithms, 11(9), https://doi.org/10.3390/a11090133. bibitem{ZZC13} Zhou Q., Zhou F., Cao F. (2013). ``A nonmonotone trust--region method based on simple conic models for unconstrained optimization", Applied Mathematics and Computation, 225, 295--305. | ||
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