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: | , , , , |
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| Format: | Conference or Workshop Item |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/11913/ http://umpir.ump.edu.my/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/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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| Summary: | 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. |
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