University of Tasmania
Browse
133136 - A generalized golden rule representative value for multiple-criteria decision analysis.pdf (2.7 MB)

A generalized golden rule representative value for multiple-criteria decision analysis

Download (2.7 MB)
journal contribution
posted on 2023-05-20, 04:15 authored by Liu, Z, Xiao, F, Lin, C-T, Byeong KangByeong Kang, Cao, Z
Multicriteria decision analysis evaluates multiple conflicting criteria in decision making, but conflicting criteria are typical in evaluating options. As the existing ordering operations involved in multicriteria decision making cannot easily be implemented with intervals, we assume that scalar representative values with intervals can effectively avoid this issue. To deal with interval-valued criteria, we propose a generalized golden rule representative value approach, which involves the sigmoid function of backpropagation neural networks to tune parameters. Our approach considers the uncertainties and side effects of the interval variables to improve individual scalar representative values. Based on numerical examples, we address the effectiveness of the proposed approach, and we provide a specific application concerning multicriteria decision making with interval criteria satisfaction.

History

Publication title

IEEE Transactions on Systems, Man, and Cybernetics: Systems

Pagination

1-12

ISSN

2168-2216

Department/School

School of Information and Communication Technology

Publisher

Institute of Electrical and Electronics Engineers

Place of publication

United States

Rights statement

Copyright 2019 IEEE.

Repository Status

  • Open

Socio-economic Objectives

Intelligence, surveillance and space

Usage metrics

    University Of Tasmania

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC