运筹与管理 ›› 2017, Vol. 26 ›› Issue (5): 151-157.DOI: 10.12005/orms.2017.0122

• 应用研究 • 上一篇    下一篇

群体信息集结过程中无量纲化方法的选择

宫诚举1,2, 郭亚军1,2, 李玲玉1,2, 李伟伟1,2   

  1. 1.东北大学 工商管理学院,辽宁 沈阳 110169;
    2.东北评价中心,辽宁 沈阳 110169
  • 收稿日期:2016-01-04 出版日期:2017-05-25
  • 作者简介:宫诚举(1991-),男,黑龙江牡丹江人,博士研究生,研究方向:综合评价理论与方法;郭亚军(1952-),男,辽宁开原人,教授,博士生导师,主要研究方向:综合评价理论与方法;李玲玉(1982-)女,辽宁锦州人,博士研究生;李伟伟(1986-),女,山东烟台人,东北大学博士后,主要研究方向:综合评价。
  • 基金资助:
    国家自然科学基金资助项目(71671031)

Dimensionless Methods Selection in the Process of Group Information Aggregation

GONG Cheng-ju1,2, GUO Ya-jun1,2, LI Ling-yu1,2, LI Wei-wei1,2   

  1. 1. School of Business Administration, Northeastern University, Shenyang 110169, China;
    2. Northeastern Comprehensive Center,Shenyang 110169, China
  • Received:2016-01-04 Online:2017-05-25

摘要: 针对线性无量纲化方法对群体评价中信息集结结果的影响问题,本文以线性加权的群体信息集结方法为背景,以集结成的群体信息最大程度地扩大被评价对象间的差异为导向,给出了群体信息集结过程中无量纲化方法选择的若干结论和建议。首先设定评价情景并提出研究假设,分析不同无量纲化方法集结成的群体信息对各被评价对象间的差异影响;然后对造成被评价对象之间差异的主要因素进行了讨论;通过对不同因素的分析以及与未经过无量纲化处理集结成的群体信息中各被评价对象间差异的比较,得出一些重要的结论,并给出一些针对群体信息结集过程中选择无量纲化方法的建议;最后,用一个算例检验了结论的有效性。

关键词: 综合评价, 群体评价, 无量纲化方法, 信息集结, 差异分析

Abstract: To analyze the problem of dimensionless methods' influence on aggregation results in group evaluation, this paper takes group information aggregation as the research background, and follows the guide of maximizing the difference among evaluation objects. It studies the choice approach of dimensionless methods in group evaluation and provides several conclusions and suggestions. Firstly, the evaluation situation is set and the research hypotheses are developed. Based on these, the differences between evaluation objects are analyzed according to the group aggregations obtained by different dimensionless methods. Secondly, we discuss the primary factors associated with the objects' difference. Some important conclusions are obtained by analyzing the above impact factors and comparing the objects' aggregations of initial data without being dimensionless. Furthermore, some suggestions about the selection of dimensionless methods in the process of group information aggregation are given. Finally, a numerical example is given to illustrate the validity of these conclusions.

Key words: comprehensive evaluation, group evaluation, dimensionless method, information aggregation, difference analysis

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