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

Yahaya, Nor Zaiazmin (2011) A New Hybrid Optimization Method Using Design Of Experiment Together With Artificial Neural Genetic Algorithm. Masters thesis, Universiti Sains Malaysia.

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Abstract

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.

Item Type: Thesis (Masters)
Subjects: T Technology > TJ Mechanical engineering and machinery > TJ1-1570 Mechanical engineering and machinery
Divisions: Kampus Kejuruteraan (Engineering Campus) > Pusat Pengajian Kejuruteraan Mekanikal (School of Mechanical Engineering) > Thesis
Depositing User: ASM Ab Shukor Mustapa
Date Deposited: 22 Feb 2019 01:04
Last Modified: 12 Apr 2019 05:26
URI: http://eprints.usm.my/id/eprint/43436

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