Quality research on the performance of a virus-evolutionary genetic algorithm for optimized sculptured surface CNC machining, through standard benchmarks

Fountas, Nikolaos A., Vaxevanidis, Nikolaos M., Stergiou, Constantinos I. and Benhadj-Djilali, Redha (2015) Quality research on the performance of a virus-evolutionary genetic algorithm for optimized sculptured surface CNC machining, through standard benchmarks. In: 9th International Quality Conference May 2015 Center for Quality, Faculty of Engineering, University of Kragujevac; 04 - 05 Jun 2015, Kragujevac, Serbia. ISBN 9788663350151

Abstract

This paper presents experimental results on a benchmark functions set, used for performance evaluation of Heuristics. Computational quality and robustness of a Virus-Evolutionary Genetic Algorithm developed to optimize manufacturing applications is assessed by conducting experiments and adjusting its intelligent operators so that its general computational behaviour is tuned up. Parameters considered include the generation number, population size, and virus infection operators.

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