A refined differential evolution algorithm for improving the performance of optimization process

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...

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Main Authors: A. R., Yusoff, Nafrizuan, Mat Yahya
Format: Conference or Workshop Item
Language:English
Published: Springer Nature 2011
Subjects:
TJ Mechanical engineering and machinery
TS Manufactures
Online Access:http://umpir.ump.edu.my/id/eprint/25563/
http://umpir.ump.edu.my/id/eprint/25563/
http://umpir.ump.edu.my/id/eprint/25563/1/A%20refined%20differential%20evolution%20algorithm%20for%20improving%20the%20performance.pdf
id ump-25563
recordtype eprints
spelling ump-255632019-12-12T05:00:10Z 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 https://doi.org/10.1007/978-3-642-25453-6_17
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic TJ Mechanical engineering and machinery
TS Manufactures
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
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.
format Conference or Workshop Item
author A. R., Yusoff
Nafrizuan, Mat Yahya
author_facet A. R., Yusoff
Nafrizuan, Mat Yahya
author_sort A. R., Yusoff
title 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_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_sort refined differential evolution algorithm for improving the performance of optimization process
publisher Springer Nature
publishDate 2011
url http://umpir.ump.edu.my/id/eprint/25563/
http://umpir.ump.edu.my/id/eprint/25563/
http://umpir.ump.edu.my/id/eprint/25563/1/A%20refined%20differential%20evolution%20algorithm%20for%20improving%20the%20performance.pdf
first_indexed 2023-09-18T22:39:19Z
last_indexed 2023-09-18T22:39:19Z
_version_ 1777416808055177216

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