Abstract
During the past few years, important scientific work has been realized concerning the use of Artificial Neural Networks (ANNs) to support decision making. ANNs offer an approach to computing which unlike conventional programming- does not necessitate a complete algorithmic specification. Firstly, this paper presents the general theoretic framework for Multiple Criteria Decision Making (MCDM) and ANNs. Further, the paper describes how ANNs can solve MCDM problems (a) with respect to the restrictions imposed by the formulation of a MCDM problem and (b) by using fuzzy systems, which can deal with uncertain and incomplete information. The decision making process of ANNs systems and the most recent scientific research related to the area is also presented. The paper concludes by pointing to some issues for future research in the field of Multicriteria Decision Making based on ANNs.
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Tigka, K.K., Zopounidis, C. (1998). Artificial Neural Networks Systems for Multiple Criteria Decision Making. In: Zopounidis, C., Pardalos, P.M. (eds) Managing in Uncertainty: Theory and Practice. Applied Optimization, vol 19. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-2845-3_19
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DOI: https://doi.org/10.1007/978-1-4757-2845-3_19
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