The General Least Square Deviation OWA Operator Problem

Dug Hun Hong and Sangheon Han
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Dug Hun Hong: Department of Mathematics, Myongji University, Yongin 449-728, Kyunggido, Korea
Sangheon Han: Department of Managment, Nagoya University of Commerce & Business, 4-4 Sagamine Komenoki, Nisshin 470-0193, Aichi, Japan

Mathematics, 2019, vol. 7, issue 4, 1-20

Abstract: A crucial issue in applying the ordered weighted averaging (OWA) operator for decision making is the determination of the associated weights. This paper proposes a general least convex deviation model for OWA operators which attempts to obtain the desired OWA weight vector under a given orness level to minimize the least convex deviation after monotone convex function transformation of absolute deviation. The model includes the least square deviation (LSD) OWA operators model suggested by Wang, Luo and Liu in Computers & Industrial Engineering, 2007, as a special class. We completely prove this constrained optimization problem analytically. Using this result, we also give solution of LSD model suggested by Wang, Luo and Liu as a function of n and α completely. We reconsider two numerical examples that Wang, Luo and Liu, 2007 and Sang and Liu, Fuzzy Sets and Systems, 2014, showed and consider another different type of the model to illustrate our results.

Keywords: decision making; OWA operator; operator weights; degree of orness; absolute disparity; least convex deviation model (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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