A New Hybrid Optimization Method Using Design Of Experiment Together With Artificial Neural Genetic Algorithm

In the engineering design process, it is a necessity to reduce the engineering design cycle time to meet the global market demand and also the customers need. Among the steps in the engineering design process, optimization process always consumed a lot of time and resources. This is because the opt...

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Main Author: Yahaya, Nor Zaiazmin
Format: Thesis
Language:English
Published: 2011
Subjects:
Online Access:http://eprints.usm.my/43436/
http://eprints.usm.my/43436/1/NOR%20ZAIAZMIN%20BIN%20YAHAYA.pdf
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author Yahaya, Nor Zaiazmin
author_facet Yahaya, Nor Zaiazmin
author_sort Yahaya, Nor Zaiazmin
building USM Institutional Repository
collection Online Access
description In the engineering design process, it is a necessity to reduce the engineering design cycle time to meet the global market demand and also the customers need. Among the steps in the engineering design process, optimization process always consumed a lot of time and resources. This is because the optimization process involved a lot of parameters and infinite solutions that required a lot of experimental runs. A new a new hybrid optimization has been developed in this research that should be able to yield higher prediction accuracy for the optimal solution and at the same time requires only a minimum number of experimental runs without compromising the prediction accuracy.
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institution Universiti Sains Malaysia
institution_category Local University
language English
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publishDate 2011
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spelling usm-434362019-04-12T05:26:30Z http://eprints.usm.my/43436/ A New Hybrid Optimization Method Using Design Of Experiment Together With Artificial Neural Genetic Algorithm Yahaya, Nor Zaiazmin TJ1-1570 Mechanical engineering and machinery In the engineering design process, it is a necessity to reduce the engineering design cycle time to meet the global market demand and also the customers need. Among the steps in the engineering design process, optimization process always consumed a lot of time and resources. This is because the optimization process involved a lot of parameters and infinite solutions that required a lot of experimental runs. A new a new hybrid optimization has been developed in this research that should be able to yield higher prediction accuracy for the optimal solution and at the same time requires only a minimum number of experimental runs without compromising the prediction accuracy. 2011-10 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/43436/1/NOR%20ZAIAZMIN%20BIN%20YAHAYA.pdf Yahaya, Nor Zaiazmin (2011) A New Hybrid Optimization Method Using Design Of Experiment Together With Artificial Neural Genetic Algorithm. Masters thesis, Universiti Sains Malaysia.
spellingShingle TJ1-1570 Mechanical engineering and machinery
Yahaya, Nor Zaiazmin
A New Hybrid Optimization Method Using Design Of Experiment Together With Artificial Neural Genetic Algorithm
title A New Hybrid Optimization Method Using Design Of Experiment Together With Artificial Neural Genetic Algorithm
title_full A New Hybrid Optimization Method Using Design Of Experiment Together With Artificial Neural Genetic Algorithm
title_fullStr A New Hybrid Optimization Method Using Design Of Experiment Together With Artificial Neural Genetic Algorithm
title_full_unstemmed A New Hybrid Optimization Method Using Design Of Experiment Together With Artificial Neural Genetic Algorithm
title_short A New Hybrid Optimization Method Using Design Of Experiment Together With Artificial Neural Genetic Algorithm
title_sort new hybrid optimization method using design of experiment together with artificial neural genetic algorithm
topic TJ1-1570 Mechanical engineering and machinery
url http://eprints.usm.my/43436/
http://eprints.usm.my/43436/1/NOR%20ZAIAZMIN%20BIN%20YAHAYA.pdf