TY - GEN
T1 - Meta-learning evolutionary artificial neural network for selecting flexible manufacturing systems
AU - Bhattacharya, Arijit
AU - Abraham, Ajith
AU - Grosan, Crina
AU - Vasant, Pandian
AU - Han, Sangyong
PY - 2006/1/1
Y1 - 2006/1/1
N2 - This paper proposes the application of Meta-Learning Evolutionary Artificial Neural Network (MLEANN) in selecting flexible manufacturing systems (FMS) from a group of candidate FMS's. First, 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, namely, design parameters, economic considerations, etc., affecting the FMS selection process in multi-criteria decision-making environment. Genetic algorithm is used to evolve the architecture and weights of the proposed neural network method. Further, a back-propagation (BP) algorithm is used as the local search algorithm. The selection of FMS is made according to the error output of the results found from the MCDM model.
AB - This paper proposes the application of Meta-Learning Evolutionary Artificial Neural Network (MLEANN) in selecting flexible manufacturing systems (FMS) from a group of candidate FMS's. First, 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, namely, design parameters, economic considerations, etc., affecting the FMS selection process in multi-criteria decision-making environment. Genetic algorithm is used to evolve the architecture and weights of the proposed neural network method. Further, a back-propagation (BP) algorithm is used as the local search algorithm. The selection of FMS is made according to the error output of the results found from the MCDM model.
UR - http://www.scopus.com/inward/record.url?scp=33745911288&partnerID=8YFLogxK
U2 - 10.1007/11760191_130
DO - 10.1007/11760191_130
M3 - Conference contribution
AN - SCOPUS:33745911288
SN - 3540344829
SN - 9783540344827
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 891
EP - 897
BT - Advances in Neural Networks - ISNN 2006
PB - Springer-Verlag Berlin Heidelberg
T2 - 3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks
Y2 - 28 May 2006 through 1 June 2006
ER -