Benchmark Studies on Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO)

The performance of a Multi-Objective Evolutionary Programming (MOEP) is significantly dependent on the parameter setting of the operator. These parameters tend to change the characteristic of adaptive in different stages of evolutionary process. The intention of this paper is to create adaptive cont...

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Main Authors:	Mahaletchumi, Morgan, Nor Rul Hasma, Abdullah, M. H., Sulaiman, Mahfuzah, Mustafa, Rosdiyana, Samad
Format:	Conference or Workshop Item
Language:	English English
Published:	2015
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/11913/ http://umpir.ump.edu.my/id/eprint/11913/7/Benchmark%20studies%20on%20Multi-Objective%20Evolutionary%20Programming%20%28MOEP%29%20using%20Mutation%20Based%20on%20Adaptive%20Mutation%20Operator%20%28AMO%29%20and%20Polynomial%20Mutation%20Operator%20%28PMO%29-abstract.pdf http://umpir.ump.edu.my/id/eprint/11913/1/Benchmark%20studies%20on%20Multi-Objective%20Evolutionary%20Programming%20%28MOEP%29%20using%20Mutation%20Based%20on%20Adaptive%20Mutation%20Operator%20%28AMO%29%20and%20Polynomial%20Mutation%20Operator%20%28PMO%29.pdf

id	ump-11913
recordtype	eprints
spelling	ump-119132018-04-11T01:30:49Z http://umpir.ump.edu.my/id/eprint/11913/ Benchmark Studies on Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO) Mahaletchumi, Morgan Nor Rul Hasma, Abdullah M. H., Sulaiman Mahfuzah, Mustafa Rosdiyana, Samad TK Electrical engineering. Electronics Nuclear engineering The performance of a Multi-Objective Evolutionary Programming (MOEP) is significantly dependent on the parameter setting of the operator. These parameters tend to change the characteristic of adaptive in different stages of evolutionary process. The intention of this paper is to create adaptive controls for each parameter existing in MOEP where it is able to improve even more the performance of the evolutionary programming. Hence, in this paper, an adaptive mutation operator based multi-objective evolutionary programming is presented. A computer program was written in MATLAB. At the end, the result was compared with the Polynomial Mutation Operator. 2015 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/11913/7/Benchmark%20studies%20on%20Multi-Objective%20Evolutionary%20Programming%20%28MOEP%29%20using%20Mutation%20Based%20on%20Adaptive%20Mutation%20Operator%20%28AMO%29%20and%20Polynomial%20Mutation%20Operator%20%28PMO%29-abstract.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/11913/1/Benchmark%20studies%20on%20Multi-Objective%20Evolutionary%20Programming%20%28MOEP%29%20using%20Mutation%20Based%20on%20Adaptive%20Mutation%20Operator%20%28AMO%29%20and%20Polynomial%20Mutation%20Operator%20%28PMO%29.pdf Mahaletchumi, Morgan and Nor Rul Hasma, Abdullah and M. H., Sulaiman and Mahfuzah, Mustafa and Rosdiyana, Samad (2015) Benchmark Studies on Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO). In: International Conference on Advanced Mechanics, Power and Energy 2015 (AMPE2015), 5 December 2015 , Hotel Holiday Inn Kuala Lumpur, Glenmarie, Shah Alam, Malaysia. . (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Mahaletchumi, Morgan Nor Rul Hasma, Abdullah M. H., Sulaiman Mahfuzah, Mustafa Rosdiyana, Samad Benchmark Studies on Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO)
description	The performance of a Multi-Objective Evolutionary Programming (MOEP) is significantly dependent on the parameter setting of the operator. These parameters tend to change the characteristic of adaptive in different stages of evolutionary process. The intention of this paper is to create adaptive controls for each parameter existing in MOEP where it is able to improve even more the performance of the evolutionary programming. Hence, in this paper, an adaptive mutation operator based multi-objective evolutionary programming is presented. A computer program was written in MATLAB. At the end, the result was compared with the Polynomial Mutation Operator.
format	Conference or Workshop Item
author	Mahaletchumi, Morgan Nor Rul Hasma, Abdullah M. H., Sulaiman Mahfuzah, Mustafa Rosdiyana, Samad
author_facet	Mahaletchumi, Morgan Nor Rul Hasma, Abdullah M. H., Sulaiman Mahfuzah, Mustafa Rosdiyana, Samad
author_sort	Mahaletchumi, Morgan
title	Benchmark Studies on Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO)
title_short	Benchmark Studies on Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO)
title_full	Benchmark Studies on Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO)
title_fullStr	Benchmark Studies on Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO)
title_full_unstemmed	Benchmark Studies on Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO)
title_sort	benchmark studies on multi-objective evolutionary programming (moep) using mutation based on adaptive mutation operator (amo) and polynomial mutation operator (pmo)
publishDate	2015
url	http://umpir.ump.edu.my/id/eprint/11913/ http://umpir.ump.edu.my/id/eprint/11913/7/Benchmark%20studies%20on%20Multi-Objective%20Evolutionary%20Programming%20%28MOEP%29%20using%20Mutation%20Based%20on%20Adaptive%20Mutation%20Operator%20%28AMO%29%20and%20Polynomial%20Mutation%20Operator%20%28PMO%29-abstract.pdf http://umpir.ump.edu.my/id/eprint/11913/1/Benchmark%20studies%20on%20Multi-Objective%20Evolutionary%20Programming%20%28MOEP%29%20using%20Mutation%20Based%20on%20Adaptive%20Mutation%20Operator%20%28AMO%29%20and%20Polynomial%20Mutation%20Operator%20%28PMO%29.pdf
first_indexed	2023-09-18T22:12:59Z
last_indexed	2023-09-18T22:12:59Z
_version_	1777415151009398784

Benchmark Studies on Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polynomial Mutation Operator (PMO)

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