Work

Similarity Analysis of Methods for Objective Determination of Weights in Multi-Criteria Decision Support Systems

Year: 2021

Type: article

Abstract: Decision support systems (DSS) are currently developing rapidly and are increasingly used in various fields. More often, those systems are inseparable from information-based systems and computer systems. Therefore, from a methodical point of view, the algorithms implemented in the DSS play a critical role. In this aspect, multi-criteria decision support (MCDA) methods are widely used. As research progresses, many MCDA methods and algorithms for the objective identification of the significance of individual criteria of the MCDA models were developed. In this paper, an analysis of available objective methods for criteria weighting is presented. Additionally, the authors presented the implementation of the system that provides easy and accessible weight calculations for any decision matrix with the possibility of comparing results of different weighting methods. The results of weighting methods were compared using carefully selected similarity coefficients to emphasise the correlation of the resulting weights. The performed research shows that every method should provide distinctive weights considering input data, emphasising the importance of choosing the correct method for a given multi-criteria decision support model and DSS.

Source: Symmetry

DOI: 10.3390/sym13101874

Authors: Bartosz Paradowski, Andrii Shekhovtsov, Aleksandra Bączkiewicz, Bartłomiej Kizielewicz, Wojciech Sałabun

Institutions: West Pomeranian University of Technology in Szczecin, University of Szczecin

Language: English

Topic: Multi-Criteria Decision Making

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $1,944

Funder: Narodowe Centrum Nauki