P., Vasant and A., Bhattacharya and A., Abraham and C., Grosan (2007) Evolutionary artificial neural network for selecting flexible manufacturing systems under disparate level-of-satisfaction of decision maker. [Citation Index Journal]
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Abstract
This paper proposes the application of Meta-Learning Evolutionary Artificial Neural Network (MLEANN) in selecting the best flexible manufacturing systems (FMS) from a group of candidate FMSs. Multi-criteria decision-making (MCDM) methodology using an improved S-shaped membership function has been developed for finding out the "best candidate FMS alternative" from a set of candidate-FMSs. The MCDM model trade-offs among various parameters, viz., design parameters, economic considerations, etc., affecting the FMS selection process under multiple, conflicting-in-nature criteria environment. The selection of FMS is made according to the error output of the results found from the proposed MCDM model.
| Item Type: | Citation Index Journal |
|---|---|
| Uncontrolled Keywords: | Flexible manufacturing systems; Hybrid approach; Meta-learning; Multi criteria decision-making; Neural networks |
| Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Departments / MOR / COE: | Departments > Computer Information Sciences |
| ID Code: | 127 |
| Deposited By: | Mr Helmi Iskandar Suito |
| Deposited On: | 02 Mar 2010 01:18 |
| Last Modified: | 19 Jan 2017 08:27 |
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