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...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
2011
|
| Subjects: | |
| Online Access: | http://eprints.usm.my/43436/1/NOR%20ZAIAZMIN%20BIN%20YAHAYA.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|