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2 Informatyka Teoretyczna i Stosowana

2 2002

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Investment project quality comparison

Dimova L., Sevastianov P.V., Figat P., Zenkova A.

Informatyka Teoretyczna i Stosowana

2002

R. 2, nr 2

35-44

Nowadays the decision-making seems as a very advanced science with fully developed mathematical tools. Unfortunately, just this circumstance "very complicated mathematical tools" is the main obstacle on the way of penetration modern scientific methods in decisionmaking practice. The aim of this article is to present on the base enough simple example the practical possibilities of a theory in a manner that perhaps seems as not very traditional, but seems more transparent and easy for persons that having need to under-take some multiobjective decisions. The main problems in formalization of decision-making process are: - existence of quantitative parameters that tan be measured by the some ways (for exam-ple, financial parameters) and qualitative parameters represented on the only verbal level (by the words). The qualitative parameters often play main role in process of decision-making; - different scales of measurements - it is known that particle criterion may refer to the dif-ferent spheres and often may be measured in incomparable units; - multiobjectivity - existence of many criteria, variables and so on, which have influence on process of decision. It is known that possibilities of a person to undertake the reasonable decisions on base of many criterions are very limited; - non-equivalence - problem of weighing (ranking) of particle criteria; - multilevel - this problem appear when each new level is based on group of parameters of lower level. The problems described above are solved by means of enough exact and of modern mathematical methods and illustrated by the concrete task of choosing the best investment project.

A probabilistic method for ordering group of intervals

Sevastianov P.V., Róg P., Karczewski K.

Informatyka Teoretyczna i Stosowana

2002

R. 2, nr 2

45-53

A probabilistic approach to the ordering of intervals is developed. The method is based on the assumption that random variables are independently and uniformly distributed at given intervals. It allows all possible cases of interval location and intersection and of ordering of interval and real number to be taken into account. Additionally, this method al-lows the widths of the intervals to be taken into account in the ordering procedure. It should be noted that the probabilistic approach was used only to infer the set of formulae needed to estimate quantitatively the degree to which one interval is less or equal to another interval. The measure of such a degree may be treated formally as one of probability, but the term "possibility" tan be also used, as it better reflects the sense of the relation between the intervals in many cases.