The Covariance Matrix Adaptation Evolution Strategy (CMAES) is widely accepted as a robust derivative-free continuous optimization algorithm for non-linear and non-convex optimization problems. CMA-ES is well known to be almost parameterless, meaning that only one hyper-parameter, the population size, is proposed to be tuned by the user. In this paper, we propose a principled approach called se...

We consider a problem in eigenvalue optimization, in particular finding a local minimizer of the spectral abscissa the value of a parameter that results in the smallest magnitude of the largest real part of the spectrum of a matrix system. This is an important problem for the stabilization of control systems. Many systems require the spectra to lie in the left half plane in order for stability ...

In this paper, an analytical method for noncircular shape extrusion is presented. Using this method, non-linear deformation field can be described with Hermit cubic spline which is prescribed by the boundary conditions of the die at its entryand exit. The upper bound method has been used to obtain optimum coefficient of the tangential boundary conditions. The results show that the optimum tange...

In this paper, an analytical method for noncircular shape extrusion is presented. Using this method, non-linear deformation field can be described with Hermit cubic spline which is prescribed by the boundary conditions of the die at its entryand exit. The upper bound method has been used to obtain optimum coefficient of the tangential boundary conditions. The results show that the optimum tange...

In this work, a non-iterative identification approach is presented for estimating a single-input single-output Wiener model, comprising an infinite impulse response discrete transfer function followed by static non-linearity. Global orthogonal basis functions and orthogonal Hermite polynomials are used as expansion bases for the linear subsystem and the non-linearity, respectively. A multi-inde...

The problem of optimal experimental design (OED) for parameter estimation of non-linear dynamic systems is considered. It is shown how this problem can be formulated as a dynamic optimization (optimal control) problem where the performance index is usually a scalar function of the Fisher information matrix. Numerical solutions can be obtained using direct methods, which transform the original p...

Recent studies in financial markets suggest that technical analysis can be a very useful tool in predicting the trend. Trading systems are widely used for market assessment however parameter optimization of these systems has adopted little concern. In this paper, to explore the potential power of digital trading, we present a new MATLAB tool based on genetic algorithms, which specializes in par...

Optimization of noisy non-linear problems plays a key role in engineering and design problems. These optimization problems can't be solved effectively by using conventional optimization methods. However, metaheuristic algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) seem very efficient to approach in these problems and became very popular. The efficiency of these ...