TY - JOUR
T1 - A new stochastic neural network model and its application to grouping parts and tools in flexible manufacturing systems
AU - Arizono, I.
AU - Ohta, H.
AU - Kato, M.
AU - Yamamoto, A.
N1 - Funding Information:
This research has supported by the Grant-in-Aid for General Scientific Research No. 03832037, Ministry ofEducation, Science and Culture in Japan. The authors would like to thank the referees for their constructive comments and suggestions in revising the paper.
PY - 1995/6
Y1 - 1995/6
N2 - 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 (FMSs).
AB - 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 (FMSs).
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U2 - 10.1080/00207549508930227
DO - 10.1080/00207549508930227
M3 - Article
AN - SCOPUS:0029326051
SN - 0020-7543
VL - 33
SP - 1535
EP - 1548
JO - International Journal of Production Research
JF - International Journal of Production Research
IS - 6
ER -