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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

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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.

Item Type: Conference or Workshop Item (Paper)
Event Title: 9th International Quality Conference May 2015 Center for Quality, Faculty of Engineering, University of Kragujevac
Organising Body: University of Kragujevac
Additional Information: Paper was published in 9th International Quality Conference : Conference manual, edited by Slavko Arsovski, Miodrag Lazic and Miladin Stefanovic, Kragujevac : Faculty of Engineering, Unviersity of Kragujevac, 2015, pp.153-160. ISBN: 9788663350151.
Physical Location: Center for Quality, Faculty of Engineering, University of Kragujevac
Research Area: Mechanical, aeronautical and manufacturing engineering
Faculty, School or Research Centre: Faculty of Science, Engineering and Computing
Faculty of Science, Engineering and Computing > School of Mechanical and Automotive Engineering
Depositing User: Nikolaos Fountas
Date Deposited: 07 Sep 2016 09:28
Last Modified: 07 Sep 2016 09:28
URI: http://eprints.kingston.ac.uk/id/eprint/32017

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