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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| Format: | Conference or Workshop Item |
| Language: | English English |
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2015
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| Online Access: | 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 |
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| 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 |
| collection | UMP |
| 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. |
| first_indexed | 2024-03-06T12:00:38Z |
| format | Conference or Workshop Item |
| id | UMPir11913 |
| institution | Universiti Malaysia Pahang |
| language | English English |
| last_indexed | 2024-03-06T12:00:38Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | UMPir119132018-04-11T01:30:49Z 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) (Unpublished) |
| 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) |
| title | 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_short | 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 |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | 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 |
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