Genetic algorithm and simulated annealing to estimate optimal process parameters of the abrasive waterjet machining

In this study, two computational approaches, Genetic Algorithm and Simulated Annealing, are applied to search for a set of optimal process parameters value that leads to the minimum value of machining performance. The objectives of the applied techniques are: (1) to estimate the minimum value of the...

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Main Authors: Mohd. Zain, Azlan, Haron, Habibollah, Sharif, Safian
Format: Article
Published: Springer London 2010
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Online Access:http://eprints.utm.my/id/eprint/26208/
http://dx.doi.org/10.1007/s00366-010-0195-5
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spelling my.utm.262082018-10-31T12:20:28Z http://eprints.utm.my/id/eprint/26208/ Genetic algorithm and simulated annealing to estimate optimal process parameters of the abrasive waterjet machining Mohd. Zain, Azlan Haron, Habibollah Sharif, Safian QA75 Electronic computers. Computer science In this study, two computational approaches, Genetic Algorithm and Simulated Annealing, are applied to search for a set of optimal process parameters value that leads to the minimum value of machining performance. The objectives of the applied techniques are: (1) to estimate the minimum value of the machining performance compared to the machining performance value of the experimental data and regression modeling, (2) to estimate the optimal process parameters values that has to be within the range of the minimum and maximum coded values for process parameters of experimental design that are used for experimental trial and (3) to evaluate the number of iteration generated by the computational approaches that lead to the minimum value of machining performance. Set of the machining process parameters and machining performance considered in this work deal with the real experimental data of the non-conventional machining operation, abrasive waterjet. The results of this study showed that both of the computational approaches managed to estimate the optimal process parameters, leading to the minimum value of machining performance when compared to the result of real experimental data. Springer London 2010 Article PeerReviewed Mohd. Zain, Azlan and Haron, Habibollah and Sharif, Safian (2010) Genetic algorithm and simulated annealing to estimate optimal process parameters of the abrasive waterjet machining. Engineering with Computers, 27 (3). 1 - 9. ISSN 0177-0667 http://dx.doi.org/10.1007/s00366-010-0195-5 DOI:10.1007/s00366-010-0195-5
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Mohd. Zain, Azlan
Haron, Habibollah
Sharif, Safian
Genetic algorithm and simulated annealing to estimate optimal process parameters of the abrasive waterjet machining
description In this study, two computational approaches, Genetic Algorithm and Simulated Annealing, are applied to search for a set of optimal process parameters value that leads to the minimum value of machining performance. The objectives of the applied techniques are: (1) to estimate the minimum value of the machining performance compared to the machining performance value of the experimental data and regression modeling, (2) to estimate the optimal process parameters values that has to be within the range of the minimum and maximum coded values for process parameters of experimental design that are used for experimental trial and (3) to evaluate the number of iteration generated by the computational approaches that lead to the minimum value of machining performance. Set of the machining process parameters and machining performance considered in this work deal with the real experimental data of the non-conventional machining operation, abrasive waterjet. The results of this study showed that both of the computational approaches managed to estimate the optimal process parameters, leading to the minimum value of machining performance when compared to the result of real experimental data.
format Article
author Mohd. Zain, Azlan
Haron, Habibollah
Sharif, Safian
author_facet Mohd. Zain, Azlan
Haron, Habibollah
Sharif, Safian
author_sort Mohd. Zain, Azlan
title Genetic algorithm and simulated annealing to estimate optimal process parameters of the abrasive waterjet machining
title_short Genetic algorithm and simulated annealing to estimate optimal process parameters of the abrasive waterjet machining
title_full Genetic algorithm and simulated annealing to estimate optimal process parameters of the abrasive waterjet machining
title_fullStr Genetic algorithm and simulated annealing to estimate optimal process parameters of the abrasive waterjet machining
title_full_unstemmed Genetic algorithm and simulated annealing to estimate optimal process parameters of the abrasive waterjet machining
title_sort genetic algorithm and simulated annealing to estimate optimal process parameters of the abrasive waterjet machining
publisher Springer London
publishDate 2010
url http://eprints.utm.my/id/eprint/26208/
http://dx.doi.org/10.1007/s00366-010-0195-5
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