Weighted aggregation systems and an expectation level-based weighting and scoring procedure
József Dombi and
Tamás Jónás
European Journal of Operational Research, 2022, vol. 299, issue 2, 580-588
Abstract:
This paper presents a novel approach to the weighted aggregation and to determination of weights in an aggregation procedure. In our study, we introduce the concept of a weighted aggregation system that consists of two components: (1) a weighting transformation and (2) an aggregation operator, both induced by a common generator function. We provide the necessary and sufficient condition for the form of a generator function-based weighted aggregation system. We show that the weighted quasi-arithmetic means on the non-negative extended real line are none other than the aggregation functions induced by weighted aggregation systems, i.e., these means are compositions of an n-ary aggregation operator and n weighting transformations (n∈N, n≥1). Next, using weighted quasi-arithmetic means on the unit interval, we introduce a new, expectation level-based weight determination method and a scoring procedure. In this method, the decision-maker’s expectation levels for the input variables are directly transformed into weights by making use of the generator function of a weighted quasi-arithmetic mean. We utilize this mean as a scoring function to evaluate the decision alternatives. Lastly, by the means of illustrative numerical examples, we present a novel decision model, in which the expectation levels can be even intervals, i.e., the weights are also intervals. Finally, we get an interval-valued score for each alternative.
Keywords: Decision support systems; Weighting transformation; Weighted quasi-arithmetic means; Expectation level; Multi-criteria decision model (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221721007414
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:299:y:2022:i:2:p:580-588
DOI: 10.1016/j.ejor.2021.08.049
Access Statistics for this article
European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati
More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().