2016
DOI: 10.1016/j.amc.2015.11.085
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Comments on a new class of nonlinear conjugate gradient coefficients with global convergence properties

Abstract: In Rivaie et al [M. Rivaie, M. Mustafa, L.W. June and I. Mohd, A new class of nonlinear conjugate gradient coefficient with global convergence properties, Appl. Math. Comp, 218(2012), 11323-11332], an efficient CG algorithm has been proposed for solving unconstrained optimization problems. However, due to a wrong inequality (3.3) used in Rivaie et al., the proof of theorem 2 and the global convergence theorem 3 are not correct. We present the necessary corrections, then the proposed method in Rivaie et al stil… Show more

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Cited by 44 publications
(46 citation statements)
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“…In addition, for large-scale unconstrained optimization problems, the conjugate gradient method (CG) is another easy but effective method, due to the two attractive features: one is the low memory requirement, the other is strong global convergence properties. In recent years, the conjugate gradient method has achieved rich results (see [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36]) from the perspective of the sufficient descent property, qausi-Newton direction and conjugacy condition. Inspired by the extension of spectral gradient method to nonlinear monotone equations, CG methods have been applied in solving the nonlinear monotone equations problem.…”
Section: Introductionmentioning
confidence: 99%
“…In addition, for large-scale unconstrained optimization problems, the conjugate gradient method (CG) is another easy but effective method, due to the two attractive features: one is the low memory requirement, the other is strong global convergence properties. In recent years, the conjugate gradient method has achieved rich results (see [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36]) from the perspective of the sufficient descent property, qausi-Newton direction and conjugacy condition. Inspired by the extension of spectral gradient method to nonlinear monotone equations, CG methods have been applied in solving the nonlinear monotone equations problem.…”
Section: Introductionmentioning
confidence: 99%
“…for all ξ i ∈ I and α i ≥ 0 with n i=1 α i = 1. Convex function has wide applications in pure and applied mathematics, physics, and other natural sciences [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]; it has many important and interesting properties [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37] such as monotonicity, continuity, and differentiability. Recently, many generalizations and extensions have been made for the convexity, for example, s-convexity [38], strong convexity [39][40][41], preinvexity [42], GA-convexity [43], GG-convexity [44], Schur convexity [45][46][47][48]…”
Section: Introductionmentioning
confidence: 99%
“…Very recently, many new inequalities such as Hermite-Hadamard type inequality [34][35][36][37][38], Petrović type inequality [39], Pólya-Szegö type inequality [40], Ostrowski type inequality [41], reverse Minkowski inequality [42], Jensen type inequality [43,44], Bessel function inequality [45], trigonometric and hyperbolic function inequalities [46], fractional integral inequality [47][48][49][50][51], complete and generalized elliptic integral inequalities [52][53][54][55][56][57], generalized convex function inequality [58][59][60], and mean value inequality [61][62][63] have been discovered by many researchers. In particular, the applications of integral inequalities have gained considerable importance among researchers for fixed-point theorems; the existence and uniqueness of solutions for differential equations [64][65][66][67][68] and numerous numerical and analytical methods have been recommended for the advancement of integral inequalities [69][70][71][72][73][74][75].…”
Section: Introductionmentioning
confidence: 99%