TL;DR
This paper presents a novel method for generating OWA weights using truncated distributions, allowing decision-makers to intuitively incorporate risk and trade-off preferences based on distribution moments.
Contribution
It introduces a new approach to determine OWA weights via truncated distributions, linking moments to decision preferences, with practical examples and analysis.
Findings
Effective weight generation based on distribution moments
Application to normal and parabolic decision spaces
Impact of criteria number on weight outcomes
Abstract
Ordered weighted averaging (OWA) operators have been widely used in decision making these past few years. An important issue facing the OWA operators' users is the determination of the OWA weights. This paper introduces an OWA determination method based on truncated distributions that enables intuitive generation of OWA weights according to a certain level of risk and trade-off. These two dimensions are represented by the two first moments of the truncated distribution. We illustrate our approach with the well-know normal distribution and the definition of a continuous parabolic decision-strategy space. We finally study the impact of the number of criteria on the results.
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