Open AccessDistortions introduced by normalisation of values of criteria in multiple criteria methods of evaluation
Author(s) -
Askoldas Podviezko
Publication year - 2014
Publication title -
lietuvos matematikos rinkinys
Language(s) - English
Resource type - Journals
eISSN - 2335-898X
pISSN - 0132-2818
DOI - 10.15388/lmr.a.2014.10
Subject(s) - multiple criteria decision analysis , attractiveness , popularity , object (grammar) , computer science , position (finance) , data mining , mathematics , artificial intelligence , mathematical optimization , psychology , social psychology , finance , psychoanalysis , economics
Quantitative multiple criteria decision aid (MCDA) methods of evaluation gain increasing popularity among researchers. The idea of the methods is to comprise values of criteria characterising each object into a single non-dimensional cumulative criterion, which reflects attractiveness or position of the object in view of an objective chosen. Normalisation of weights is a compulsory procedure whenever criteria of different dimensions are present. There several methods of normalisation available. Nevertheless, each method may introduce distortions into transformed data. The paper is devoted to exploration of problems related to such distortions and reveals particular cases.