Article ID: | iaor19952041 |
Country: | United Kingdom |
Volume: | 33 |
Issue: | 6 |
Start Page Number: | 1535 |
End Page Number: | 1548 |
Publication Date: | Jun 1995 |
Journal: | International Journal of Production Research |
Authors: | Ohta H., Arizono I., Kato M., Yamamoto A. |
Keywords: | neural networks |
Recently, some stochastic neural network models have been presented for the purpose of overcoming the defect that the deterministic neural network models do not have the ability to escape from a local optimal solution. However, the specification of the values of various parameters and weights in these stochastic neural network models is more complicated than that in the deterministic neural network models. In this paper, a new stochastic neural network model is proposed in order to reduce the complication of specifying the values of parameters and weights. For a practical purpose, the proposed model is applied to the problem of grouping parts and tools in flexible manufacturing systems.