<p>The Modeling of problem situations is a very important issue in decision-making theory. Actually, there are no decision support systems which include decision making methods under risk and uncertainty. The main advantage of a proposed approach is the ability to process dependences and feedbacks which may exist between conditions, sub-conditions and their realizations.</p><p>http://dx.doi.org/10.13033/ijahp.v3i1.81</p>
The paper is focused on searching for novel methods aimed at improving the performance and usability of a common decision-making process where a panel of experts are assisted by specialized software systems. An equivalent exchange method (EEM) is considered in the paper as a potential candidate for a versatile method applicable in expert decision-making process for solving problems in various subject domains. The method is formally described in the paper in the form of an iterative algorithm where each iteration leads to the reduce in the number of alternatives under consideration until it converges to the preferable one. The key feature of EEM consists in the fact that the original comparison between multiple alternatives described by many attributes measured in different units is replaced by the sequence of simple exchanges between pairs of alternatives where only two attributes are engaged at once. The numerical example illustrating the full run of the algorithm is thoroughly described, so the actions performed in the steps of the algorithm are explained. The case of the successful implementation of EEM as the module of Expert Decision Support System is also presented.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.