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一种基于模糊理论和可信度机制的多准则决策方法用于物流中心选址

A multicriteria decision making approach based on fuzzy theory and credibility mechanism for logistics center location selection.

作者信息

Wang Bowen, Xiong Haitao, Jiang Chengrui

机构信息

School of Computer Science and Information Engineering, Beijing Technology and Business University, Beijing 100048, China.

School of Computer Science and Information Engineering, Beijing Technology and Business University, Beijing 100048, China ; School of Computer Science and Engineering, Beihang University, Beijing 100191, China ; Collaborative Innovation Centre for State-Owned Assets Administration, Beijing 100048, China.

出版信息

ScientificWorldJournal. 2014;2014:347619. doi: 10.1155/2014/347619. Epub 2014 Aug 19.

Abstract

As a hot topic in supply chain management, fuzzy method has been widely used in logistics center location selection to improve the reliability and suitability of the logistics center location selection with respect to the impacts of both qualitative and quantitative factors. However, it does not consider the consistency and the historical assessments accuracy of experts in predecisions. So this paper proposes a multicriteria decision making model based on credibility of decision makers by introducing priority of consistency and historical assessments accuracy mechanism into fuzzy multicriteria decision making approach. In this way, only decision makers who pass the credibility check are qualified to perform the further assessment. Finally, a practical example is analyzed to illustrate how to use the model. The result shows that the fuzzy multicriteria decision making model based on credibility mechanism can improve the reliability and suitability of site selection for the logistics center.

摘要

作为供应链管理中的一个热门话题,模糊方法已广泛应用于物流中心选址,以提高物流中心选址在定性和定量因素影响方面的可靠性和适用性。然而,它没有考虑到专家在前期决策中的一致性和历史评估准确性。因此,本文通过将一致性优先级和历史评估准确性机制引入模糊多准则决策方法,提出了一种基于决策者可信度的多准则决策模型。通过这种方式,只有通过可信度检查的决策者才有资格进行进一步评估。最后,通过一个实例分析来说明如何使用该模型。结果表明,基于可信度机制的模糊多准则决策模型可以提高物流中心选址的可靠性和适用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d88/4152960/fc7e3f9e7126/TSWJ2014-347619.001.jpg

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