A refined differential evolution algorithm for improving the performance of optimization process
Various Artificial Intelligent (AI) algorithms can be applied in solving optimization problems. Among the latest Evaluation Algorithm (EA) have been developed is Differential Evolution (DE). DE is developed based on an improved Genetic Algorithm and come with different strategies for faster optimiza...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
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Springer Nature
2011
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/25563/1/A%20refined%20differential%20evolution%20algorithm%20for%20improving%20the%20performance.pdf |
| _version_ | 1825812816311877632 |
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| author | A. R., Yusoff Nafrizuan, Mat Yahya |
| author_facet | A. R., Yusoff Nafrizuan, Mat Yahya |
| author_sort | A. R., Yusoff |
| collection | UMP |
| description | Various Artificial Intelligent (AI) algorithms can be applied in solving optimization problems. Among the latest Evaluation Algorithm (EA) have been developed is Differential Evolution (DE). DE is developed based on an improved Genetic Algorithm and come with different strategies for faster optimization. However, the population trapped in local optimality and premature convergence to cause in DE algorithm have cause poor performance during optimization process. To overcome the drawbacks, mixed population update and bounce back strategy were introduced to modify and improve current DE algorithm. A Himmelblau function and real case from engineering problem were used to show the performance improvements of refined DE in optimization process. |
| first_indexed | 2024-03-06T12:34:44Z |
| format | Conference or Workshop Item |
| id | UMPir25563 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T12:34:44Z |
| publishDate | 2011 |
| publisher | Springer Nature |
| record_format | dspace |
| spelling | UMPir255632019-12-12T05:00:10Z http://umpir.ump.edu.my/id/eprint/25563/ A refined differential evolution algorithm for improving the performance of optimization process A. R., Yusoff Nafrizuan, Mat Yahya TJ Mechanical engineering and machinery TS Manufactures Various Artificial Intelligent (AI) algorithms can be applied in solving optimization problems. Among the latest Evaluation Algorithm (EA) have been developed is Differential Evolution (DE). DE is developed based on an improved Genetic Algorithm and come with different strategies for faster optimization. However, the population trapped in local optimality and premature convergence to cause in DE algorithm have cause poor performance during optimization process. To overcome the drawbacks, mixed population update and bounce back strategy were introduced to modify and improve current DE algorithm. A Himmelblau function and real case from engineering problem were used to show the performance improvements of refined DE in optimization process. Springer Nature 2011 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/25563/1/A%20refined%20differential%20evolution%20algorithm%20for%20improving%20the%20performance.pdf A. R., Yusoff and Nafrizuan, Mat Yahya (2011) A refined differential evolution algorithm for improving the performance of optimization process. In: International Conference on Informatics Engineering and Information Science (ICIEIS 2011) , 14-16 November 2011 , Kuala Lumpur. pp. 184-194., 252 (2). ISSN 1865-0929 ISBN 978-364225452-9 (Published) https://doi.org/10.1007/978-3-642-25453-6_17 |
| spellingShingle | TJ Mechanical engineering and machinery TS Manufactures A. R., Yusoff Nafrizuan, Mat Yahya A refined differential evolution algorithm for improving the performance of optimization process |
| title | A refined differential evolution algorithm for improving the performance of optimization process |
| title_full | A refined differential evolution algorithm for improving the performance of optimization process |
| title_fullStr | A refined differential evolution algorithm for improving the performance of optimization process |
| title_full_unstemmed | A refined differential evolution algorithm for improving the performance of optimization process |
| title_short | A refined differential evolution algorithm for improving the performance of optimization process |
| title_sort | refined differential evolution algorithm for improving the performance of optimization process |
| topic | TJ Mechanical engineering and machinery TS Manufactures |
| url | http://umpir.ump.edu.my/id/eprint/25563/1/A%20refined%20differential%20evolution%20algorithm%20for%20improving%20the%20performance.pdf |
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