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中国管理科学 ›› 2019, Vol. 27 ›› Issue (12): 143-151.doi: 10.16381/j.cnki.issn1003-207x.2019.12.014

• 论文 • 上一篇    下一篇

基于Mo-RVIKOR的混合多属性决策方法

潘亚虹, 耿秀丽   

  1. 上海理工大学管理学院, 上海 200093
  • 收稿日期:2018-01-26 修回日期:2018-06-12 出版日期:2019-12-20 发布日期:2019-12-30
  • 通讯作者: 耿秀丽(1984-),女(汉族),山东东营人,上海理工大学管理学院,副教授,博士,研究方向:产品服务系统、设计理论与方法和决策理论与方法,E-mail:xiuliforever@163.com. E-mail:xiuliforever@163.com
  • 基金资助:
    国家自然科学基金资助项目(71301104);教育部人文社会科学研究规划基金资助项目(19YJA630021);高等学校博士学科点专项科研基金资助课题(20133120120002)

Hybrid Multiple Attribute Decision Making Approach based on Mo-RVIKOR

PAN Ya-hong, GENG Xiu-li   

  1. Business School, University of Shanghai for Science and Technology, Shanghai 200093, China
  • Received:2018-01-26 Revised:2018-06-12 Online:2019-12-20 Published:2019-12-30

摘要: 针对复杂性和不确定性多属性决策问题,考虑定量和定性融合的属性形式,提出了模块化随机多准则妥协解排序法(Modular Random VlseKriterijumska Opti-mizacija I Kompromisno Resenje,Mo-RVIKOR),该方法无需将信息统一,就能处理多种信息形式存在的多属性决策问题。采用精确数、随机变量处理定量评价信息,用概率语义术语集处理定性评价信息;通过改进离差最大化法确定属性权重;根据Mo-RVIKOR对决策对象进行排序;最后以某公司C2B定制化服务质量评测项目为例,验证了所提方法的有效性。

关键词: 混合多属性决策, VIKOR, 改进离差最大化法, 概率语义集

Abstract: Hybrid multiple attribute decision making(MADM) problems have broad applications in the fields of economy, management and social science, etc. The existing methods to support hybrid MADM are more and more common which can process many different types of information such as crisp, interval, fuzzy, hesitant fuzzy. However, hybrid information is often converted into the same form which leads to the loss of information in most of these methods. In addition, only few research concerned the uncertainty caused by random variable. Aiming to avoid any transformation step and take random variable into account, Modular Random VlseKriterijumska Opti-mizacija I Kompromisno Resenje (Mo-RVIKOR) is proposed which can break heterogeneous information into modules and process information in a straightforward way without unifying. Firstly, real numbers and random variable are used by experts to process quantitative evaluation information, probabilistic linguistic term set to process qualitative evaluation information. Secondly, the weights of attribute are determined by the improved deviation maximization method. Finally, Mo-RVIKOR is adopted to rank the alternatives. This method can effectively handle certain or uncertain mixed evaluation information, and a case study of C2B customized service quality assessment of one company is presented to illustrate the effectiveness of the proposed approach.

Key words: hybrid multi-attribute decision-making, VIKOR, improved deviation maximum method, probabilistic linguistic term set

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