Decision making is associated with ranking problems aimed to obtain a set of preference order of solutions. People can make mistakes choosing the best object for investments. Due to high cost of such mistakes, such a choice should be well founded. This paper presents multicriteria method for choosing the best object, called SNOD (Scale of Normalized and Ordered Differences). There are two stages in the method: preliminary formal analysis of given alternatives, performed entirely by a computer, and Decision Maker preferences elicitation. The method is based on a Verbal Decision Analysis approach. The possibility of criteria interdependence is taken into account.
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The need to combine data and experts' knowledge in order to solve omplex and ill-structured decision problems is a major concern in the modern arketing and management science. In this paper, the functionality óf an intelligent Decision Support System, named MARKEX, is presented. The system acts as a consultant for marketers, providing visual support to enhance understanding and to overcome lack of expertise. MARKEX incorporates partial knowledge bases to support decision-makers in different stages of the product development process. The data bases Eof the system are the results of consumer surveys, as well as financial information of the enterprises involved in the decision making process. The system's model base encompasses statistical and data analysis, preference analysis, and consumer choice models.
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This paper presents a multicriteria decision support methodology for selecting sites to be inspected within the framework of arms control in Europe (conventional forces). We present our formulation of the problem focusing on the construction criteria. Then, we develop a multicriteria aggregation procedure designed to rank the sites by decreasing order or priority. In order to derive robust prescriptions, we propose a general and original approach integrating imprecision and ill-determination preference information.
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