<p>In this article we have derived two versions, ξk and ρk were derived from an algorithm based on the first suggested modified Fletcher-Reeves method in the article for the two-term CG method and another term to get a downward search towards the function minimum point with the search for an inaccurate line and we have proved rapprochement. These two algorithms combined with the Cuckoo algorithm to achieve a remarkable performance in reducing the number of repetitions in order to reach the minimization of 10 functions is unconstrained in the numerical results.</p><p> </p>
<p>In this article, a combined optimization algorithm was proposed which combines the optimal adaptive Cuckoo algorithm (OACS) which is Nature-inspired algorithm with Gray Wolf optimizer algorithm (GWO). Sometimes considering the cuckoo algorithm alone, may fail to find the local minimum-point and also fails to reach to the solution because of the slow speed of its convergence property. Therefore, considering the new proposed adaptive combined algorithm gave a strong improvement for using this to reach the minimum point in solving (23) nonlinear test problems. This is suitable to solve a large number of nonlinear unconstraint optimization test functions with obtaining good and robust numerical results.</p>
This article considers modified formulas for the standard conjugate gradient (CG) technique that is planned by Li and Fukushima. A new scalar parameter θkNew for this CG technique of unconstrained optimization is planned. The descent condition and global convergent property are established below using strong Wolfe conditions. Our numerical experiments show that the new proposed algorithms are more stable and economic as compared to some well-known standard CG methods.
In this work, we tend to deal within the field of the constrained optimization methods of three-term Conjugate Gradient (CG) technique which is primarily based on Dai–Liao (DL) formula. The new proposed technique satisfies the conjugacy property and the descent conditions of Karush–Kuhn–Tucker (K.K.T.). Our planned constrained technique uses the robust Wolfe line search condition with some assumptions. We tend to prove the global convergence property of the new planned technique. Numeral comparisons for (30-thirty) constrained optimization issues make sure the effectiveness of the new planned formula.
<span>In this article, we give a new modification for the Dai-Liao method to solve monotonous nonlinear problems. In our modification, we relied on two important procedures, one of them was the projection method and the second was the method of damping the quasi-Newton condition. The new approach of derivation yields two new parameters for the conjugated gradient direction which, through some conditions, we have demonstrated the sufficient descent property for them. Under some necessary conditions, the new approach achieved global convergence property. Numerical results show how efficient the new approach is when compared with basic similar classic methods.</span>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.