A new approach for criteria weight elicitation of the ARAS-H method

• Authors: Ghram Maroua , Moalla Frikha Hela
• Languages of publication: EN

Abstracts

EN

Criteria weight inference is a crucial step for most of multi-criteria methods. However, criteria weights are often determined directly by the decision-maker (DM) which makes the results unreliable. Therefore, to overcome the imprecise weighting, we suggest the use of the preference programming technique. Instead of obtaining criteria weights directly from the DM, we infer them in a more objective manner to avoid the subjectivity and the unreliability of the results. Our aim is to elicit the ARAS-H criteria weights at each level of the hierarchy tree via mathematical programming, taking into account the DM’s preferences. To put it differently, starting from preference information provided by the DM, we proceed to model our constraints. The ARAS-H method is an extension of the classical ARAS method for the case of hierarchically structured criteria. We adopt a bottom-up approach in order to elicit ARAS-H criteria weights, that is, we start by determining the elementary criteria weights (i.e. the criteria at the lowest level of the hierarchy tree). The solution of the linear programs is obtained using LINGO software. The main contribution of our criteria weight elicitation procedure is in overcoming imprecise weighting without excluding the DM from the decision making process.

Keywords

EN

ARAS-H; Criteria weights; Mathematical programming; Multiple Criteria Decision Aiding; Preference disaggregation

• Publisher: Uniwersytet Ekonomiczny w Katowicach
• Journal: Multiple Criteria Decision Making
• Year: 2021
• Volume: 16
• Pages: 89-109

Contributors

author

Ghram Maroua

• Laboratory “Optimisation, Logistique et Informatique Décisionnelle” (OLID), University of Sfax, Higher Institute of Industrial Management of Sfax

author

Moalla Frikha Hela

• Laboratory “Optimisation, Logistique et Informatique Décisionnelle” (OLID), University of Sfax, Higher Institute of Industrial Management of Sfax

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Identifiers

ISSN

2084-1531