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

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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Bibliographic Details
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

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