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EN
The Analytic Hierarchy Process (AHP) is the method that supports people’s decisions in the multi-criteria decision making problems. In this method the decision process is based on pairwise comparing of every two possible alternatives. The decision maker (DM) compares alternatives by choosing an appropriate “linguistic phrase” or a number from a proper set. This set of “linguistic phrases” and/or the numbers connected with them are referred to as the priority scale. There are several different scales that are described in literature and used in AHP practice. In dependence of the scale chosen by the DM, the final decisions might differ. In the AHP it is assumed that DMs make mistakes over comparing pairs of alternatives, but it was also observed that the assumed scale increases these errors as well. In our paper, we investigate the impact of the adopted scale to the number and magnitude of errors in the final decision. Our results show that the choice of the scale has a big impact on the final decision, so it is crucial part of AHP. It turns out that scales with bigger resource of options result in better evaluations of priority vectors.
EN
The Analytic Hierarchy Process (AHP) is perhaps the most popular approach to decision-making problems of prioritization. The basis of the AHP is pairwise comparison, which is used to compare alternatives. This comparisons are provided by decision makers usually as linguistic expressions which are next converted to numbers from a fixed set called a scale. The influence of the scale on the quality of prioritization was investigated in a number of papers. One of the most important types of judgment scale is the Geometric Scale. Its elements depend on specific parameters. In this paper, the impact of the choice of this scale’s parameters on errors in priority vectors and on values of the inconsistency indices is studied via Monte Carlo simulations.
EN
This article is devoted to some problems connected with multicriteria decision analysis. We consider the relationship between the pairwise comparison matrix (PCM) and a priority vector (PV) obtained on the basis of this matrix. The PCM elements are the decision makers’ judgments about priority ratios i.e. the ratios of weights contained in the PV. It is known, that in the case of consistent matrix, we can obtain the exact value of related PV. However, the real-world practice shows that the decision maker does not create a perfectly consistent PCM, and thus usually in such a matrix the judgment’s errors occur. In our paper we use Monte Carlo simulation to study the relationship between various possible distributions of these errors and the distributions of the errors in estimates of the true PV. In these simulation we apply some initial families distribution and some different parameters. We obtain interesting results which show very slight influence families distribution on final PV errors. Our paper show that much bigger influence on simulation result have adopted parameters than selection distribution family.
EN
Advantages from usage of replaceable bodies system. Mounting and installation of replaceable bodies. List of body types. Logistic components.
EN
Specification and technical data of individual units. Comparision with their foreign counterparts.
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