中国安全科学学报 ›› 2024, Vol. 34 ›› Issue (2): 217-224.doi: 10.16265/j.cnki.issn1003-3033.2024.02.0581

• 应急技术与管理 • 上一篇    下一篇

基于云-TOPSIS法的应急物流供应商综合评价

黄国平(), 雷皓翔**()   

  1. 湖南工业大学 商学院,湖南 株洲 412007
  • 收稿日期:2023-08-20 修回日期:2023-11-21 出版日期:2024-02-28
  • 通讯作者:
    ** 雷皓翔(1995—),男,甘肃平凉人,硕士研究生,研究方向为应急物流工程与管理。E-mail:
  • 作者简介:

    黄国平 (1970—),男, 湖南安仁人,博士,副教授,主要从事应急物流工程与管理方面的研究。E-mail:

  • 基金资助:
    湖南省社会科学成果评审委员会项目(XSP20YBC354)

Comprehensive evaluation of emergency logistics suppliers based on cloud TOPSIS method

HUANG Guoping(), LEI Haoxiang**()   

  1. School of Business,Hunan University of Technology, Zhuzhou Hunan 412007, China
  • Received:2023-08-20 Revised:2023-11-21 Published:2024-02-28

摘要:

为实现应急物流降本增效的目标,从供应商层面出发,运用云-逼近理想解排序法(TOPSIS)评价应急物流供应商综合能力;根据应急物流特点,从应急响应能力、物资质量、成本控制、应急响应柔性、企业内外部条件等5方面,构建应急物流供应商综合评价指标体系;借鉴博弈论思想,将用改进熵权法求得的客观权重和用层次分析法(AHP)求得的主观权重作为博弈对手,确定最优组合权重;运用云模型量化指标决策云和加权云对供应商的模糊定性评价语义;采用TOPSIS法构建正负理想解集合,计算备选方案与正负理想解的距离确定相对贴近度,确定最优备选方案。研究结果表明:指标决策云能准确地将评价语言量化,云-TOPSIS法的评价结果更合理;在供应商相对贴近度排序中,采用云-TOPSIS法计算的最优与最劣者差值为0.331 5,而TOPSIS法为0.088 2,两者相差0.243 3,表明云-TOPSIS法的评价结果区分度更大,能更直观地辅助决策者做出最优选择。

关键词: 云模型, 逼近理想解排序法(TOPSIS), 应急物流, 供应商, 综合评价

Abstract:

In order to achieve the goal of cost reduction and efficiency enhancement in emergency logistics, the comprehensive capabilities of emergency logistics suppliers were evaluated from the perspective of suppliers by utilizing the Cloud TOPSIS. Based on the characteristics of emergency logistics, a comprehensive evaluation index system for emergency logistics suppliers was constructed from five aspects: emergency response capability, material quality, cost control, emergency response flexibility, and internal and external conditions of the enterprise. Drawing on the ideas of game theory, the objective weights obtained by the improved entropy weight method and the subjective weights obtained by Analytic Hierarchy Process (AHP) were taken as game opponents to determine the optimal combination of weights. The cloud model was used to solve for the decision-making cloud of indicators and the weighted cloud for the fuzzy qualitative evaluation semantics quantification of suppliers. Finally, using the TOPSIS method, the positive and negative ideal solution sets were constructed, and the relative closeness to these ideal solutions was determined by calculating the distance of alternative solutions, thus identifying the optimal alternative. Research indicates that the Indicator Decision Cloud can accurately quantify evaluative language, and the results of the Cloud-TOPSIS method are more reasonable. In the ranking of suppliers' relative closeness, the difference between the best and worst calculated by the Cloud-TOPSIS method is 0.331 5, while for the TOPSIS method, it is 0.088 2, with a difference of 0.243 3. This suggests that the evaluation results of the Cloud-TOPSIS method have a greater degree of differentiation, which can more intuitively assist decision-makers in making optimal choices.

Key words: cloud model, technique for order preference by similarity to ideal solution (TOPSIS), emergency logistics, supplier, comprehensive evaluation

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