GnIOWA operators and some weights allocation methods with their properties. Issue 5 (17th February 2021) - Jin, LeSheng; Chen, Zhen‐Song; Yager, Ronald R.; Špirkovà, Jana; Mesiar, Radko; Paternain, Daniel; Bustince, Humberto
Abstract: 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.