Search results for "Weighted sum model"
showing 3 items of 3 documents
Decision-aid for discrete multiple criteria decision making problems with imprecise data
1999
Abstract We describe ways of aiding decision making with a discrete set of alternatives. In many decision situations, it is not possible to obtain explicit preference information from the decision makers. Instead, useful decision-aid can be provided to the decision makers by describing what kind of weighting of the criteria result in certain choices of the alternatives. The suggested treatment is based on the basic ideas of the ELECTRE III method. The modelling of the preferences by pseudo-criteria is especially helpful in case the data, that is, the criterion values are imprecise. Unlike ELECTRE III, no ranking of the alternatives is produced. Based on a minimum-procedure in the exploitati…
Further Developments and Tests of a Progressive Algorithm for Multiple Criteria Decision Making
1993
P. Korhonen, H. Moskowitz, and J. Wallenius (1986) developed a progressive algorithm and the supporting theory for modeling and solving multiple criteria decision problems with discrete alternatives. A special feature of the algorithm is that it relaxes the usual assumption of a fixed set of available decision alternatives and complete knowledge of a decision maker's (DM's) preference structure or value function. The algorithm is based on progressively sampling the decision space, obtaining preference information from the DM, determining the likelihood of finding possibly/surely better alternatives, and based on this information, continuing the search or terminating it by making the final …
Two ways to handle dependent uncertainties in multi-criteria decision problems☆
2009
Abstract We consider multi-criteria group decision-making problems, where the decision makers (DMs) want to identify their most preferred alternative(s) based on uncertain or inaccurate criteria measurements. In many real-life problems the uncertainties may be dependent. In this paper, we focus on multicriteria decision-making (MCDM) problems where the criteria and their uncertainties are computed using a stochastic simulation model. The model is based on decision variables and stochastic parameters with given distributions. The simulation model determines for the criteria a joint probability distribution, which quantifies the uncertainties and their dependencies. We present and compare two…