Abstract
The modified Terstoun method is proposed as a solution for selecting the best alternative among m options, where each alternative is assessed using the numeric scalar function F(Ai), defining the integral numerical evaluation of quality. This method, rooted in probability theory, introduces random variables f(Ai) that are independently and normally distributed, capturing integral quality characteristics. Through statistical studies, including sensitivity analyses to distribution variations and expert parameterizations, the method's critical aspects are explored, highlighting its effectiveness within certain constraints while pointing towards potential refinements and alternative methodologies for improved decision-making processes.
Keywords (in English)
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