Absolute order-of-magnitude reasoning applied to a social multi-criteria evaluation framework

Abstract

A social multi-criteria evaluation framework for solving a real-case problem of selecting a wind farm location in the regions of Urgell and Conca de Barberá in Catalonia (northeast of Spain) is studied. This paper applies a qualitative multi-criteria decision analysis approach based on linguistic labels assessment able to address uncertainty and deal with different levels of precision. This method is based on qualitative reasoning as an artificial intelligence technique for assessing and ranking multi-attribute alternatives with linguistic labels in order to handle uncertainty. This method is suitable for problems in the social framework such as energy planning which require the construction of a dialogue process among many social actors with high level of complexity and uncertainty. The method is compared with an existing approach, which has been applied previously in the wind farm location problem. This approach, consisting of an outranking method, is based on Condorcet's original method. The results obtained by both approaches are analysed and their performance in the selection of the wind farm location is compared in aggregation procedures. Although results show that both methods conduct to similar alternatives rankings, the study highlights both their advantages and drawbacks.

Keywords:

• absolute order-of-magnitude
• multi-criteria decision analysis
• linguistic labels
• qualitative reasoning
• TOPSIS
• energy planning

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was partially supported by the SENSORIAL Research Project [TIN2010-20966-C02-01], [TIN2010-20966-C02-02], and the Research Project [HAR2010-20684-C02-01], both funded by the Spanish Ministry of Science and Information Technology. Partial support was also provided by a doctoral fellowship awarded to one of the authors at the ESADE Business School, with additional support from Ramon Llull University.