Araştırma Makalesi
BibTex RIS Kaynak Göster

Yıl 2018, Cilt: 1 Sayı: 2, 91 - 99, 21.01.2019
https://izlik.org/JA37AX63CC

Öz

Kaynakça

  • [1] N. Andrei , New hybrid conjugate gradient algorithms for unconstrained optimization, Enc. Mat. Sci., 2009 2560-2571.[2] N. Andrei, An unconstrained optimization test function collection, Adv. Model. Optim., 10(1) 2008, 147-161.[3] I. Bongartz, A. Conn, N. Gould and P. Toint, Constrained and unconstrained testing envi-ronment, J. Optim. Theory Appl., 21(1), 1993, 123–160 [4] Y. Dai and Y. Yuan, A nonlinear conjugate gradient method with a strong global con-vergence property, SIAM J. Optimiz., 10(1) 1999, 177-182.[5 L. C. W. Dixon, Nonlinear optimisation: A survey of the state of the art, Hatfield Polytech-nic. Numerical Optimisation Centre (1973). [6] D. Dolan and J. Moré, Benchmarking optimization software with performance profiles, Math. Program., 91(2) 2002, 201-213.[7] E. K. Chong and S. H. Zak, An introduction to optimization, John Wiley & Sons 2013. [8] R. Fletcher and C. M. Reeves, Function minimization by Conjugate gradients, comput. J., 7(2) 1964, 149-154.[9] W. Hager and H. Zhang , A survey of nonlinear conjugate gradient methods, Pac. J. Op-tim., 2(1) 2006, 35-58.[10] M. Hestenes and E. Stiefel, Methods of conjugate Gradients For solving linear systems, J. Res. Nat. Bur. Stand., 49(1) 1952. [11] K. K. Abbo and L. A. Abdulwahid, Generalized Dai-Yuan non-linear conjugate gradi-ent method for unconstrained optimization, Int. J. Sci. Math. Educ., 8(6) 2017, 17993-17999. [12] X. Li and X. Zhao, A hybrid conjugate gradient method for optimization problems, Nat. Sci., 3(1) 2011, 85. [13] Y. Liu and C. Story, Efficient generalized conjugate gradient algorithms, part l : Theory, J. Optimiz. Theory App., 69(1) 1991, 129-137. [14] J. Nocedal and J. Wright, Numerical Optimization, Springer Series in Operations Re-search, Springer Verlag, New York, 2006. [15] E. Polak and G. Ribiere, Note sur la convergence de méthodes de directions conjuguées, Rev. Fr. Inform. Rech. O., 3(16) 1969, 35-43.[16] S. S. Djordjević, New hybrid conjugate gradient method as a convex combination of FR and PRP Methods. Filomat, 30(11) 2016, 3083-3100. [17] P. Wolfe, Convergence conditions for ascent methods, SIAM rev., 11(2) 1969, 226-235.

New Hybrid Conjugate Gradient Method as a Convex Combination of Liu-Storey and Dixon Methods

Yıl 2018, Cilt: 1 Sayı: 2, 91 - 99, 21.01.2019
https://izlik.org/JA37AX63CC

Öz

In this paper we consider a new
hybrid conjugate gradient algorithm, which is convex combination of the
Liu-Story algorithm and Dixon algorithm, the descent property and global
convergence are proved for the new suggested method. Numerical comparisons show
that the present method often behaves better than Liu-Storey and Dixon methods. 

Kaynakça

  • [1] N. Andrei , New hybrid conjugate gradient algorithms for unconstrained optimization, Enc. Mat. Sci., 2009 2560-2571.[2] N. Andrei, An unconstrained optimization test function collection, Adv. Model. Optim., 10(1) 2008, 147-161.[3] I. Bongartz, A. Conn, N. Gould and P. Toint, Constrained and unconstrained testing envi-ronment, J. Optim. Theory Appl., 21(1), 1993, 123–160 [4] Y. Dai and Y. Yuan, A nonlinear conjugate gradient method with a strong global con-vergence property, SIAM J. Optimiz., 10(1) 1999, 177-182.[5 L. C. W. Dixon, Nonlinear optimisation: A survey of the state of the art, Hatfield Polytech-nic. Numerical Optimisation Centre (1973). [6] D. Dolan and J. Moré, Benchmarking optimization software with performance profiles, Math. Program., 91(2) 2002, 201-213.[7] E. K. Chong and S. H. Zak, An introduction to optimization, John Wiley & Sons 2013. [8] R. Fletcher and C. M. Reeves, Function minimization by Conjugate gradients, comput. J., 7(2) 1964, 149-154.[9] W. Hager and H. Zhang , A survey of nonlinear conjugate gradient methods, Pac. J. Op-tim., 2(1) 2006, 35-58.[10] M. Hestenes and E. Stiefel, Methods of conjugate Gradients For solving linear systems, J. Res. Nat. Bur. Stand., 49(1) 1952. [11] K. K. Abbo and L. A. Abdulwahid, Generalized Dai-Yuan non-linear conjugate gradi-ent method for unconstrained optimization, Int. J. Sci. Math. Educ., 8(6) 2017, 17993-17999. [12] X. Li and X. Zhao, A hybrid conjugate gradient method for optimization problems, Nat. Sci., 3(1) 2011, 85. [13] Y. Liu and C. Story, Efficient generalized conjugate gradient algorithms, part l : Theory, J. Optimiz. Theory App., 69(1) 1991, 129-137. [14] J. Nocedal and J. Wright, Numerical Optimization, Springer Series in Operations Re-search, Springer Verlag, New York, 2006. [15] E. Polak and G. Ribiere, Note sur la convergence de méthodes de directions conjuguées, Rev. Fr. Inform. Rech. O., 3(16) 1969, 35-43.[16] S. S. Djordjević, New hybrid conjugate gradient method as a convex combination of FR and PRP Methods. Filomat, 30(11) 2016, 3083-3100. [17] P. Wolfe, Convergence conditions for ascent methods, SIAM rev., 11(2) 1969, 226-235.
Toplam 1 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Matematik
Bölüm Araştırma Makalesi
Yazarlar

Khalil Abbo Bu kişi benim

Nehal Hameed Bu kişi benim

Yayımlanma Tarihi 21 Ocak 2019
IZ https://izlik.org/JA37AX63CC
Yayımlandığı Sayı Yıl 2018 Cilt: 1 Sayı: 2

Kaynak Göster

APA Abbo, K., & Hameed, N. (2019). New Hybrid Conjugate Gradient Method as a Convex Combination of Liu-Storey and Dixon Methods. Journal of Multidisciplinary Modeling and Optimization, 1(2), 91-99. https://izlik.org/JA37AX63CC
AMA 1.Abbo K, Hameed N. New Hybrid Conjugate Gradient Method as a Convex Combination of Liu-Storey and Dixon Methods. jmmo. 2019;1(2):91-99. https://izlik.org/JA37AX63CC
Chicago Abbo, Khalil, ve Nehal Hameed. 2019. “New Hybrid Conjugate Gradient Method as a Convex Combination of Liu-Storey and Dixon Methods”. Journal of Multidisciplinary Modeling and Optimization 1 (2): 91-99. https://izlik.org/JA37AX63CC.
EndNote Abbo K, Hameed N (01 Ocak 2019) New Hybrid Conjugate Gradient Method as a Convex Combination of Liu-Storey and Dixon Methods. Journal of Multidisciplinary Modeling and Optimization 1 2 91–99.
IEEE [1]K. Abbo ve N. Hameed, “New Hybrid Conjugate Gradient Method as a Convex Combination of Liu-Storey and Dixon Methods”, jmmo, c. 1, sy 2, ss. 91–99, Oca. 2019, [çevrimiçi]. Erişim adresi: https://izlik.org/JA37AX63CC
ISNAD Abbo, Khalil - Hameed, Nehal. “New Hybrid Conjugate Gradient Method as a Convex Combination of Liu-Storey and Dixon Methods”. Journal of Multidisciplinary Modeling and Optimization 1/2 (01 Ocak 2019): 91-99. https://izlik.org/JA37AX63CC.
JAMA 1.Abbo K, Hameed N. New Hybrid Conjugate Gradient Method as a Convex Combination of Liu-Storey and Dixon Methods. jmmo. 2019;1:91–99.
MLA Abbo, Khalil, ve Nehal Hameed. “New Hybrid Conjugate Gradient Method as a Convex Combination of Liu-Storey and Dixon Methods”. Journal of Multidisciplinary Modeling and Optimization, c. 1, sy 2, Ocak 2019, ss. 91-99, https://izlik.org/JA37AX63CC.
Vancouver 1.Abbo K, Hameed N. New Hybrid Conjugate Gradient Method as a Convex Combination of Liu-Storey and Dixon Methods. jmmo [Internet]. 01 Ocak 2019;1(2):91-9. Erişim adresi: https://izlik.org/JA37AX63CC