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Weights determination of OWA operators by parametric identification
- Source :
- Mathematics and Computers in Simulation, Mathematics and Computers in Simulation, Elsevier, 2008, 77 (5-6), pp.499-511. ⟨10.1016/j.matcom.2007.11.024⟩
- Publication Year :
- 2008
- Publisher :
- Elsevier BV, 2008.
-
Abstract
- This contribution presents a new approach on weights determination in industrial decision making aided by OWA operators. Multi-criteria decision aid is a good way, for an industrialists, to determine his preferred compromise products, in the case of risk products or innovative products. The multi-criteria decision support chosen is the Ordered Weighted Average (OWA) operators, introduced by Yager [R.R. Yager, On ordered weighted averaging aggregation operators in multicriteria decision making, IEEE Trans. Syst. Man Cybern. 18 (1988) 183-190]. The interest of this aggregation method is, beyond its simplicity of use, product evaluation according unique scale. Furthermore, the weights are not fixed by criterion but according to utility level. First, a learning sample is ranked by the decision-maker. Then, this ranked sample is used in order to determine the weights by parametric identification. For this, an hypothesis of equipartition of the scores of each sample is used. An industrial application, from a food production, illustrates this approach. The ranks obtained from several samples are compared.
- Subjects :
- 0209 industrial biotechnology
Mathematical optimization
Decision support system
Weighted sum model
General Computer Science
Scale (descriptive set theory)
Sample (statistics)
02 engineering and technology
Theoretical Computer Science
020901 industrial engineering & automation
OWA
multi-criteria analysis
[INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering
0202 electrical engineering, electronic engineering, information engineering
Fuzzy number
Mathematics
Numerical Analysis
Applied Mathematics
Weighted product model
fuzzy numbers
parametric identification
Modeling and Simulation
Product (mathematics)
020201 artificial intelligence & image processing
Weighted arithmetic mean
weights of criteria
Subjects
Details
- ISSN :
- 03784754
- Volume :
- 77
- Database :
- OpenAIRE
- Journal :
- Mathematics and Computers in Simulation
- Accession number :
- edsair.doi.dedup.....b01ca7608437ed2b486f1d2d22f7d7a2