Open AccessBayesian approach for criteria weights recalculation
Author(s) -
Irina Vinogradova
Publication year - 2020
Publication title -
lietuvos matematikos rinkinys
Language(s) - English
Resource type - Journals
eISSN - 2335-898X
pISSN - 0132-2818
DOI - 10.15388/lmr.b.2015.09
Subject(s) - multiple criteria decision analysis , topsis , selection (genetic algorithm) , bayesian probability , computer science , expert opinion , decision maker , group decision making , artificial intelligence , mathematics , machine learning , management science , operations research , engineering , psychology , medicine , intensive care medicine , social psychology
Multiple Criteria Decision Making (MCDM) methods are effectively used in decision making tasks. The weights of criteria are an integral part of MCDM methods. The paper proposes the Bayesian approach to recalculate the weights of the criteria, when the decision-maker takes into account the opinions of other expert groups. Recalculation is relevant when the selection is individualized by the opinion of separate expert group. In this paper the distance learning course was chosen by separate group of experts, using SAW and TOPSIS methods and recounted criteria weights by Bayesian method.