Repository logo
 
No Thumbnail Available
Publication

Testing Nelder-Mead Based Repulsion Algorithms for Multiple Roots of Nonlinear Systems via a Two-Level Factorial Design of Experiments

Use this identifier to reference this record.
Name:Description:Size:Format: 
ART_GiselaRamadas_2015_DMA.pdf507.02 KBAdobe PDF Download

Advisor(s)

Abstract(s)

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.

Description

Keywords

Algorithms Nonlinear systems Experimental design Factorial design Analysis of variance Reflection Neurophysiology Optimization

Citation

Research Projects

Organizational Units

Journal Issue

Publisher

Plos

CC License

Altmetrics