Visual Analysis of Evolutionary Optimization Algorithms

Abstract

Growing application of evolutionary optimization algorithms in the problems of different domain have led to analyze their efficiency and effectiveness rigorously. Various approaches have been proposed to algorithms for performance evaluation such as parametric, non-parametric or mathematical which lack direct involvement of results obtained. A visual comparative performance evaluation method has been proposed in this paper incorporating more direct participation of results. Proposed method has been studied in perspective of three types of comparisons one-to-one, one-to-many and many-to-many. Necessary interpretations for the method have been illustrated and examined with solutions obtained on several benchmark functions through well known evolutionary optimization algorithms. © 2014 IEEE.