relation: https://khub.utp.edu.my/scholars/276/
title: Evolutionary artificial neural network for selecting flexible manufacturing systems under disparate level-of-satisfaction of decision maker
creator: Bhattacharya, A.
creator: Abraham, A.
creator: Vasant, P.
creator: Grosan, C.
description: 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.
publisher: IJICIC Editorial Office
date: 2007
type: Article
type: PeerReviewed
identifier:   Bhattacharya, A. and Abraham, A. and Vasant, P. and Grosan, C.  (2007) Evolutionary artificial neural network for selecting flexible manufacturing systems under disparate level-of-satisfaction of decision maker.  International Journal of Innovative Computing, Information and Control, 3 (1).  pp. 131-140.  ISSN 13494198     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-38049061772&partnerID=40&md5=828f2e8eaeb8da9b97e57e6d254e667f