 Neural network application for fuzzy multi-criteria decision making problemsDavood Golmohammadi International Journal of Production Economics, 2011, vol. 131, issue 2, 490-504 Abstract: In this paper, a fuzzy multi-criteria decision making model is presented based on a feed forward artificial neural network. This model is used to capture and represent the decision makers' preferences. The topology of the neural network model is developed to train the model. The proposed model can use historical data and update the database information for alternatives over time for future decisions. Basically, multi-criteria decision making problems are formulated, and neural network is used to learn the relation among criteria and alternatives and rank the alternatives. We do not use any utility function for the modeling; however, a unique method is proposed for eliciting the information from decision makers. The proposed model is applicable for a wide variety of multi-attribute decision making problems and can be used for future ranking or selection without managers' judgment effort. Simulation of the managers' decisions is demonstrated in detail and the design and implementation of the model are illustrated by a case study. Keywords: Neural; networks; Decision; making; Fuzzy; sets (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:131:y:2011:i:2:p:490-504 Access Statistics for this article International Journal of Production Economics is currently edited by Stefan Minner More articles in International Journal of Production Economics from Elsevier |
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