对DEA中效率相同的有效和无效dmu进行全面排序

Q3 Business, Management and Accounting

International Journal of Business Performance and Supply Chain Modelling Pub Date : 2019-07-10 DOI:10.1504/IJBPSCM.2019.10022632

M. Ghiyasi

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引用次数: 5

摘要

数据包络分析(DEA)是一种计算一组决策单元(dmu)相对效率的数学规划方法。在效率测量过程后，一些dmu可能具有相同的效率测量，特别是一些dmu可能被发现是有效的。问题是，在一组具有相同效率度量的DMU中，哪个DMU表现更好。本文旨在通过DMU对相关集团的帮助以及对整个生产系统的帮助来回答这个问题。这产生了两个排名指数。第一个指标用于用相同的效率度量对低效的dmu进行排序，第二个指标用于对高效的dmu进行排序。将所提出的方法与文献中已知的排名指标进行了比较，并通过许多数值例子和实际数据说明了所提出的方法。

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Full ranking of efficient and inefficient DMUs with the same measure of efficiency in DEA

Data envelopment analysis (DEA) is a mathematical programming approach for calculating the relative efficiency of a group of decision making units (DMUs). After efficiency measurement process some DMUs may have the same measure of efficiency, specifically some DMUs may be found efficient. The question is which DMU performs better within a group of DMUs with the same measure of efficiency. The current article aims to answer this question based the DMU's aid not only to the associated group but also its aid to the whole production system. This yields to two ranking indices. The first index is for ranking inefficient DMUs with the same measure of efficiency and the second index is for ranking efficient DMUs. A comparison between the proposed approaches and well-known ranking index in the literature is provided and proposed approaches are explained by many numerical examples and a real life data illustration.

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来源期刊

International Journal of Business Performance and Supply Chain Modelling Business, Management and Accounting-Business and International Management

CiteScore

2.00

自引率

0.00%

发文量

期刊介绍： IJBPSCM covers original, high-quality and cutting-edge research on all aspects of supply chain modelling, aiming at bridging the gap between theory and practice with applications analysing the real situation to improve business performance. Topics covered include Business performance modelling, strategy Vendor/supplier selection, supplier development, purchasing management Supply chain management (SCM), green supply chain modelling Reverse logistics, closed loop/knowledge-based supply chains, 3PL/4PL Sustainable/quality based/agile/leagile/intelligent SCM Supply chain performance/optimisation/risk/decision making/support systems AI, information sharing in SCM, systems approach to SCM Coordinated/global/flexible SCM, risk mitigation strategies Stochastic supply chain games IT-enabled SCM, fuzzy modelling, data mining Supply chain network management, modelling/simulation, implementation Training/education, information security, RFID Supply chain analysis, transportation decisions, vehicle routing, bullwhip effect Logistics in disaster management Cross-country comparison.