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GnIOWA operators and some weights allocation methods with their properties
Author(s) -
Jin LeSheng,
Chen ZhenSong,
Yager Ronald R.,
Špirkovà Jana,
Mesiar Radko,
Paternain Daniel,
Bustince Humberto
Publication year - 2021
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.22382
Subject(s) - monotone polygon , mathematics , regular polygon , mathematical optimization , type (biology) , computer science , ecology , biology , geometry
This study proposes some standard and general forms of induced ordered weighted averaging (GnIOWA) operators where the inductive information is ordered weighted averaging (OWA) weight vectors instead of real numbers. It shows the usefulness of such type of generalized induced OWA in decision‐making and evaluation and many other applications. We propose three weights allocation methods that are specifically designed for the proposed GnIOWA operators. For each of the proposed weights allocation methods, a numerical example is also attached accordingly. With the use of convex/concave Regular Increasing Monotone quantifiers, we further discuss some mathematical properties of these weights allocation methods.
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