The aim of this work is to present a new hybrid algorithm for the Molecular Docking problem: Variable Genetic Operator Search (VGOS). The proposed method combines an Evolutionary Algorithm with Variable Neighborhood Search. Experimental results show that the algorithm is able to achieve good results, in terms of energy optimization and RMSD values for several molecules when compared with previo...

In this work some interesting relations between results on basic optimization and algorithms for nonconvex functions (such as BFGS and secant methods) are pointed out. In particular, some innovative tools for improving our recent secant BFGS-type and LQN algorithms are described in detail. © 2006 Elsevier B.V. All rights reserved. MSC: 51M04; 65H20; 65F30; 90C53

Recently, Al-Baali (2014) has extended the damped-technique in the modified BFGS method of Powell (1978) for Lagrange constrained optimization functions to the Broyden family of quasi-Newton methods for unconstrained optimization. Appropriate choices for the damped-parameter, which maintain the global and superlinear convergence property of these methods on convex functions and correct the Hess...

A Hessian matrix in full waveform inversion (FWI) is difficult to compute directly because of high computational cost and an especially large memory requirement. Therefore, Newton-like methods are rarely feasible in realistic largesize FWI problems. We modify the BFGS method to use a projected Hessian matrix that reduces both the computational cost and memory required, thereby making a quasiNew...

In this paper we propose a parallel preconditioner for the Newton method in the computation of the leftmost eigenpairs of large and sparse symmetric positive definite matrices. A sequence of preconditioners starting from an enhanced approximate inverse RFSAI [13] and enriched by a BFGS-like update formula is proposed to accelerate the Preconditioned Conjugate Gradient solution of the linearized...

We consider the numerical solution of an inverse problem of finding the shape and location of holes in an elastic body. The problem is solved by minimizing a functional depending on the eigenvalues and traces of corresponding eigenmodes. We use the adjoint method to calculate the shape derivative of this functional. The optimization is performed by BFGS, using a genetic algorithm as a preproces...

The Bregman method is utilized to quantitatively improve the simultaneous reconstruction of absorption and scattering coefficients for both Jacobian-based and gradient-based methods in quantitative photoacoustic tomography with multiple optical excitations. It is the synergistic combination of Bregman method and the total-variation regularization in achieving the desired quantitative improvemen...

We propose an iterative method that solves a nonsmooth convex optimization problem by converting the original objective function to a once continuously differentiable function by way of Moreau-Yosida regularization. The proposed method makes use of approximate function and gradient values of the MoreauYosida regularization instead of the corresponding exact values. Under this setting, Fukushima...