模糊环境下VIKOR方法在质量管理顾问选择中的应用

Q4 Business, Management and Accounting

International Journal of Multicriteria Decision Making Pub Date : 2014-04-15 DOI:10.1504/IJMCDM.2014.060423

G. Kabir

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引用次数: 7

摘要

顾问等机构在全面质量管理(TQM)计划的成功实施中扮演着重要的角色，并帮助组织获得竞争优势。一般来说，许多因素影响合适的顾问选择问题，坚持不确定和不精确的数据，通常来自公司不同职能领域的几个人参与这个过程。本文将VIKOR方法与模糊集理论相结合，建立了一种改进的、更有效的TQM顾问选择模型。语言等级用梯形模糊数表示，以评估这些因素的等级和权重。最后给出了一个数值例子来说明该模型的应用。

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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Consultant selection for quality management using VIKOR method under fuzzy environment

Meditating entities such as consultants can play an important role in successful total quality management (TQM) programme implementation and helps the organisations to attain competitive advantage. In general, many factors affect the appropriate consultant selection problem which adheres to uncertain and imprecise data, and usually several people from different functional areas of the company are involved in this process. In this paper, an improved and more effective TQM consultant selection model has been developed through integrating VIKOR method with fuzzy set theory. Linguistic ratings are expressed in trapezoidal fuzzy numbers to assess the ratings and weights for these factors. A numerical example is proposed to illustrate an application of the proposed model.

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来源期刊

International Journal of Multicriteria Decision Making Business, Management and Accounting-Strategy and Management

CiteScore

0.70

自引率

0.00%

发文量

期刊介绍： IJMCDM is a scholarly journal that publishes high quality research contributing to the theory and practice of decision making in ill-structured problems involving multiple criteria, goals and objectives. The journal publishes papers concerning all aspects of multicriteria decision making (MCDM), including theoretical studies, empirical investigations, comparisons and real-world applications. Papers exploring the connections with other disciplines in operations research and management science are particularly welcome. Topics covered include: -Artificial intelligence, evolutionary computation, soft computing in MCDM -Conjoint/performance measurement -Decision making under uncertainty -Disaggregation analysis, preference learning/elicitation -Group decision making, multicriteria games -Multi-attribute utility/value theory -Multi-criteria decision support systems and knowledge-based systems -Multi-objective mathematical programming -Outranking relations theory -Preference modelling -Problem structuring with multiple criteria -Risk analysis/modelling, sensitivity/robustness analysis -Social choice models -Theoretical foundations of MCDM, rough set theory -Innovative applied research in relevant fields