[PDF] Top 20 A modified nonmonotone BFGS algorithm for unconstrained optimization

... Newton equation (.) also contains both gradient and function value information, and it has been proved that the new formula has a higher order approximation to ∇  f (x). Fur- thermore, Yuan et al. [] extended a ... See full document

... Its solution has been appealed to many peoples to do it. People created many algorithms aiming at question (P1) and presented some methods as the trust region method; Newton method; DFP method and BFGS method and ... See full document

... the unconstrained minimization problems with Alternating Direction Nonmonotone Approximate Newton ...the unconstrained minimizer into the box { w ∈ R m : l ≤ ≤ w u } , The second subprob- lem is a ... See full document

... of unconstrained optimization problems from [18], which indicates the proposed method possesses better performances when compared with the classic PRP method, CG-DESCENT method and DSP-CG ...our ... See full document

... already modified an algorithm by [10] to solve an unconstrained optimization problems using the principle of optimal designs of experiment where the step length is obtained by taking the ... See full document

... In this paper, a new inexact line search rule is presented, which is a modified version of the classical Armijo line search rule. With lower cost of computation, a larger descent magnitude of objective function is ... See full document

... Barzilai-Borwein method performs quite well if compared to steepest descent method. However, Barzilai-Borwein method sometimes presents problems because all algorithms of this method have to start at origin. Unlike ... See full document

... a modified CSA, which integrates an accelerated searching strategy in its ...the optimization of several ...The modified CSA, specifically, the adaptive cuckoo search algorithm (ASCA), is ... See full document

... the Modified Bonferroni Correction is adopted while performing the t-test (Karaboga & Akay, ...proposed algorithm and the other algorithm is less than the significance ratio then it indicates the ... See full document

... Powell) algorithm, and BFGS (Broyden, Fletcher, Goldfarb, Shanno) algorithm formula, the similar search process is obtained, which is shown in ... See full document

... the nonmonotone technique as proposed in [2, 3], and uses a slight modification of the secant condition in [7] for constructing an approximation of the Hessian at the current ...a modified version of the ... See full document

... From the numerical experiment on the quasi-Newton methods, it is proved that the BFGS method is the most successful one among all the quasi-Newton methods. But the global convergence for general function f is ... See full document

... Plenty of hybrid conjugate gradient methods were presented in [–] after the first hy- brid conjugate algorithm was proposed by Touati-Ahmed and Storey []. In [], Lu et al. proposed a new hybrid conjugate ... See full document

... large-scale unconstrained optimization problems (see Buckley and Le Nir [3], Liu and Nocedal [11], Gilbert and Lemar´echal [6], and Byrd, Nocedal, and ...standard BFGS method, the only di ff erence is ... See full document

... solving optimization problems more efficiently: cooperative coevolution (CC) algorithms and non-decomposition ...divides optimization problems into subcomponents and solves these components independently, ... See full document

... Algorithm 1 is a generalization of the quasi-Newton method for minimizing the locally Lipschitz continuous function. In Section 5, we describe a line search algorithm how to find a step length along the ... See full document

... In mathematics, Newton's method is an iterative method for finding roots of equations. In optimization, Newton's method is specialized to find stationary points of differentiable functions, which are the zeros of ... See full document

... an algorithm based on modified particle swarm optimization (MPSO) and modified discrete particle swarm optimization (MDPSO) has been successfully employed to solve the multi objective ... See full document

... Genetic Algorithm (GA) and Particle Swarm Optimization ...hybrid algorithm is also proposed with the combination of PSO and Broyden Fletcher Goldfarb Shanno Algorithm ...as optimization ... See full document

... based optimization algorithm known as Sine Cosine Algorithm (SCA), in contrast to meta-heuristics; main feature is randomization having a relevant role in both exploration and exploitation in ... See full document