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The OWA Weights of Improved Minimax Disparity Model
Author(s) -
Tohidi G.,
Khodadadi M.
Publication year - 2015
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.21711
Subject(s) - minimax , ranking (information retrieval) , simplex , preference , operator (biology) , rank (graph theory) , mathematical optimization , computer science , mathematics , algorithm , artificial intelligence , combinatorics , statistics , biochemistry , chemistry , repressor , transcription factor , gene
One of the critical and prerequisite issues in the ordered weighted averaging (OWA) operator applications is the determination of the OWA operator weights. To this end, this paper removes some of the constraints of the improved minimax disparity (MD) model and obtains its optimal simplex tableau in the general case (i.e., for any level of orness and n ), and then for the desired n introduces n − 1 optimal basic feasible solutions of the model. The study also presents the weights of the preference ranking aggregation system without solving any model and suggests a secondary goal model for selecting a unique preference ranking aggregation weights through the alternative optimal weights of the improved MD model. The usefulness of the proposed methods is indicated by using an application to rank Ph.D. candidates.