A fuzzy MCDM model for knowledge service vendor evaluation and selection

2010 Third International Symposium on Knowledge Acquisition and Modeling Pub Date : 2010-11-29 DOI:10.1109/KAM.2010.5646150

Liyu Zhu

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引用次数: 7

Abstract

Knowledge service vendor selection is an important task for the decision makers of the company in the knowledge economics. The purpose of this study is to investigate a fuzzy multiple criteria decision-making method for evaluating and selecting knowledge service vendor. In the paper, the multiple criteria should consider in the evaluation and selection process is presented. Then, a fuzzy MCDM approach based on fuzzy TOPSIS is proposed. The linguistic evaluation information given by the decision makers are transformed into the form of triangular fuzzy numbers. Based on the extended TOPSIS, the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS) are determined. The relative closeness of each alternatives to the FPIS and FNIS is calculated to determine the ranking order of all alternatives. The evaluation results of the knowledge service providers can be obtained through the proposed fuzzy method and then the proper vendor can be selected. Additionally, an illustrating example is given to show the feasibility and practicability of the proposed approach.

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知识服务供应商评价与选择的模糊MCDM模型

知识服务供应商的选择是知识经济时代企业决策者的一项重要任务。本研究的目的是探讨一种模糊多准则决策方法来评估和选择知识服务供应商。本文提出了在评价和选择过程中应考虑的多重标准。然后，提出了一种基于模糊TOPSIS的模糊MCDM方法。将决策者给出的语言评价信息转化为三角模糊数的形式。在扩展TOPSIS的基础上，确定了模糊正理想解和模糊负理想解。计算每个备选方案与FPIS和FNIS的相对接近程度，以确定所有备选方案的排名顺序。通过所提出的模糊方法，可以得到知识服务提供者的评价结果，从而选择合适的供应商。最后，通过实例说明了所提方法的可行性和实用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2010 Third International Symposium on Knowledge Acquisition and Modeling

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