文章摘要
基于VIKOR的再制造服务供应商选择决策方法
VIKOR-based decision-making method for remanufacturing service supplier selection
投稿时间:2017-03-13  
DOI:
中文关键词: 再制造服务  供应商选择  VIKOR方法  多准则群决策  模糊数  熵权法
英文关键词: remanufacturing service  supplier selection  VIKOR method  multi-criteria group decision-making  fuzzy number  entropy weight method
基金项目:国家自然科学基金资助项目(71471143);武汉科技大学冶金矿产资源高效利用与造块湖北省重点实验室开放基金资助项目(2016zy013).
作者单位E-mail
夏绪辉 武汉科技大学机械传动与制造工程湖北省重点实验室,湖北 武汉,430081 xiaxuhui@wust.edu.cn 
胡俊峰 武汉科技大学机械传动与制造工程湖北省重点实验室,湖北 武汉,430081  
王蕾 武汉科技大学机械传动与制造工程湖北省重点实验室,湖北 武汉,430081  
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中文摘要:
      再制造服务是实现产品多生命周期的重要运行管理模式之一。本文针对再制造服务活动及其组合方式,构建了一种以供应商匹配决策为主导的三阶段再制造服务过程模型。为解决供应商决策中评价信息的复杂性和不易量化的问题,引入区间数、语言变量、模糊数等多种数据类型进行信息描述,保持了数据的真实性和实用性;针对主、客观两种评价准则下的混合数据类型评价信息,运用VIKOR方法对备选方案择优排序,克服了混合数据的不可公度性和数据转换导致的失真问题,得到的妥协最优解更符合企业实际需求;运用信任函数和熵权法来确定决策者和各准则的权重,避免主观赋权的二次不确定性。最后通过算例和敏感性分析验证了所提出的供应商选择方法的可行性和稳定性。
英文摘要:
      Remanufacturing service is one of the most important operation management modes to realize product multi-lifecycle. This paper builds a supplier matching decision-making oriented three-stage remanufacturing service process model for the remanufacturing service activities and their combinations. Since evaluation information of the vendors is complex and difficult to quantify, in order to keep its authenticity and practicality, a variety of data types such as interval number, linguistic variable and fuzzy number are used to describe this information. In view of the two types of evaluation criteria including objective and subjective ones and the evaluation information with mixed data types, VIKOR method is used to rank and select the alternatives. Thus the incommensurability of mixed data and the distortion in data conversion are solved, and the compromised optimal solution is more suitable for the actual requirements of the enterprises. To avoid the second uncertainty of subjective weight assignment, belief function and entropy weight method are applied to determine the weights of each decision maker and criterion. Finally, the feasibility and stability of the proposed method for supplier selection are verified by numerical example and sensitivity analysis.
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