Statistical Analysis of Optimization Algorithms With R

Based on experiences from several (rather theoretical) tutorials and workshops devoted to the experimental analysis of algorithms at the world's leading conferences in the field of Computational Intelligence, a practical, hands-on tutorial for the statistical analysis of optimization algorithms is presented. This tutorial -demonstrates how to analyze results from real experimental studies, e.g., experimental studies in EC -item gives a comprehensive introduction in the R language -item introduces the powerful GUI "rstudio" (http://rstudio.org) -exemplifies the analysis using SPOT (http://cran.r-project.org/web/packages/SPOT/) R is the most attractive and fastest growing open source computer language for statistical computing and graphics in the world. It provides a wide variety of statistical and graphical techniques: linear and nonlinear modeling, statistical tests, time series analysis, classification, clustering, etc. R is distributed over CRAN (http://cran.r-project.org), which is a network of ftp and web servers around the world that store identical, up-to-date, versions of code and documentation for R.