MCDM'05 - paper no. 4


 

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Multicriteria decision aid under uncertainty

Cezary Dominiak

Abstract:

Decision making under uncertainty implies that in certain situations a person does not have the information which adequately describes, prescribes or predicts a system, its behavior or other characteristics, deterministically and numerically. Thus uncertainty is related to a state of the human mind, i.e. lack of complete knowledge about something. In the paper Multicriteria Decision Aid under Uncertainty (C. Dominiak) the author considers the "traditionally understood" problem of decision making under uncertainty and therefore he assumes that the probabilities of the stated of nature are not know. A discrete set of alternatives and a discrete set of scenarios have been selected for the purpose of evaluating alternatives. A dominance relation for the type of problem considered in the paper is proposed. This relation enables us to define the optimal solution and en efficient one. Next, free decision aiding procedures are introduced: the hierarchy and quasi-hierarchy procedure, decision aiding on the basis of distance function procedure, and interactive multi-criteria decision aiding procedure. Each method is illustrated by a simple numerical example.

Reference index:

Cezary Dominiak, (2006), Multicriteria decision aid under uncertainty, Multiple Criteria Decision Making (1), pp. 63-82

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Scopus citations in 3 paper(s):
  1. Gaspars-Wieloch, H. (2014). Modifications of the Hurwicz's decision rule. Central European Journal of Operations Research, 22(4), 779-794. doi:10.1007/s10100-013-0302-y
  2. Gaspars-Wieloch, H. (2017). A decision rule based on goal programming and one-stage models for uncertain multi-criteria mixed decision making and games against nature. Croatian Operational Research Review, 8(1), 61-76. doi:10.17535/crorr.2017.0004
  3. Labreuche, C., & Destercke, S. (2019). How to handle missing values in multi-criteria decision aiding? Paper presented at the IJCAI International Joint Conference on Artificial Intelligence, , 2019-August 1756-1763.