Histograms for Comparing Evolutionary Algorithms

Last Friday we were discussing the paper by Tirronen and Weber, “Sparkline Histograms for Comparing Evolutionary Algorithms“, presented at IJCCI 2010. This work proposes histograms that represent the distribution of values in the set of results for comparing the performance of Evolutionary Algorithms. Such a visual comparison provides a quick evaluation of the relative performance of the algorithms in a test set, as well as the overall performance of each one. Some patterns of the histograms permit to identify features such as lack of robustness, high rate of convergence to local optima, and high standard deviation. Altough this method does not replace numerical and statistical comparisons, it may be helpfull in the analysis of Evolutionary Algorithms, so we suggest you to take a look at the work of Tirronen and Weber.

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Carlos M. Fernandes was born in Luanda in 1973 and lives in between Lisbon, Portugal, and Granada, Spain. He graduated (Technical University of Lisbon, 1998) in Electrotechnics Engineering and owns a master degree in the same field since 2002 (Technical University of Lisbon). He is currently pursuing a Ph.d. on Bio-inspired Computing. From 2001 to 2005 he was an assistant at Instituto Politécnico de Setúbal. (He is also a photographer and photography teacher.) Bio-inspired Computing is his major field of research: Genetic Algorithms, Estimation of Distribution Algorithms, Ant Colony Optimization, Particle Swarm Optimization and other metaheuristics. He is particularly interested in the hybridization of Bio-inspired Computing techniques with Self-Organization, Self-Organized Criticality Models and diversity maintenance strategies. In the present, Dynamic Optimization Problems are his mains target for applying such techniques. website: www.carlosmfernandes.com email: c.m.fernandes.photo@gmail.com

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