淡江大學機構典藏:Item 987654321/126867
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 64178/96951 (66%)
造访人次 : 10526617      在线人数 : 17850
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧：
  • 您可在西文检索词汇前后加上"双引号"，以获取较精准的检索结果
  • 若欲以作者姓名搜寻，建议至进阶搜寻限定作者字段，可获得较完整数据
    •  进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/126867


    题名: Resolving Rank Reversal in TOPSIS: A Comprehensive Analysis of Distance Metrics and Normalization Methods
    作者: Shyur, Huan-Jyh;Shih, Hsu-Shih
    关键词: ranking reversal;TOPSIS;normalization;distance metric;extreme alternative
    日期: 2024.12
    上传时间: 2025-03-20 09:28:04 (UTC+8)
    出版者: Vilnius University Institute of Data Science and Digital Technologies
    摘要: This paper examines ranking reversal (RR) in Multiple Criteria Decision Making (MCDM) using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Through a mathematical analysis of min-max and max normalization techniques and distance metrics (Euclidean, Manhattan, and Chebyshev), the study explores their impact on RR, particularly when new, high-performing alternatives are introduced. This research provides insight into the causes of RR, offering a framework that clarifies when and why RR occurs. The findings help decision-makers select appropriate techniques, promoting more consistent and reliable outcomes in real-world MCDM applications.
    關聯: Informatica 35( 4)， p. 837-858
    DOI: 10.15388/24-INFOR576
    显示于类别:[資訊管理學系暨研究所] 期刊論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    index.html0KbHTML17检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈