Neuro-genetic impact on cell formation methods of Cellular Manufacturing System design: A quantitative review and analysis
| Autor: | Manojit Chattopadhyay, Pranab K. Dan, Tamal Ghosh, Sitanath Mazumdar, Sourav Sengupta |
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| Rok vydání: | 2013 |
| Předmět: |
Soft computing
General Computer Science Artificial neural network Computer science business.industry Cellular manufacturing General Engineering Machine learning computer.software_genre Group technology Quantitative analysis (finance) Genetic algorithm Systems design Artificial intelligence Cluster analysis business computer |
| Zdroj: | Computers & Industrial Engineering. 64:256-272 |
| ISSN: | 0360-8352 |
| DOI: | 10.1016/j.cie.2012.09.016 |
| Popis: | This paper presents a quantitative review of the influence and the impact of the two major soft computing approaches, Artificial Neural Network and Genetic Algorithm on cell formation methods of the design of Cellular Manufacturing System (CMS). An in-depth analysis has been carried out to identify the research trend, for the last two decades that captures the chronological progress and continuous improvement in the design of CMS. The in-depth quantitative analysis helped to identify the trend of research, improvements over the years and the capability of the soft-computing approaches to handle complex data-sets with different objective functions. The comparative study of the computational time, number of cells formed and the clustering efficiency obtained, helped to figure out the success rates of each approach and the progress achieved since early 1990s till recent times. |
| Databáze: | OpenAIRE |
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