摘要
针对汽车零部件供应商评价中存在的问题,根据目前汽车零部件供应商评价中指标赋权方法的特点,构建了基于组合赋权TOPSIS的供应商评价模型。在此过程中,提出了一种将主客观权重进行组合的算法——Kullback散度算法。组合后的权重体现了评价指标的客观信息和主观信息,使评价结果更加可靠、可信。给出了实证分析,验证了该方法的有效性。
For the present problem of automotive parts supplier evaluation, according to characters of index weights method of automotive supplier evaluation, the TOPSIS model based on combination weighting is built. In this process, we propose a combination algorithm which combines subjective and objective weights, namely Kullback algorithm, and the combined weight reflects information in both of subjective and objective, and make the result of evaluation more reliable and credible. A case study is given, which shows that the method introduced in this paper is feasible.
出处
《重庆理工大学学报(自然科学)》
CAS
2013年第11期14-19,共6页
Journal of Chongqing University of Technology:Natural Science