基于价值的数据包络分析:分段线性规划方法

Q4 Business, Management and Accounting International Journal of Multicriteria Decision Making Pub Date : 2014-03-24 DOI:10.1504/IJMCDM.2014.059963
D. Despotis, Dimitris Sotiros
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引用次数: 3

摘要

将价值判断纳入数据包络分析(DEA)是一个广泛的方法框架,有助于推动效率评估符合个人偏好。基于价值的DEA是最近发展起来的,它利用多标准决策分析(MCDA)的价值评估协议,将原始输入/输出数据转换为价值尺度。在此背景下,我们引入了一种分段线性规划方法来求解基于值的DEA,该方法采用数据转换-变量变更技术和保证区域约束。我们通过回顾以前的效率评估研究得出的文献概述我们的方法。
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Value-based data envelopment analysis: a piece-wise linear programming approach
Incorporating value judgments in data envelopment analysis (DEA) is a broad methodological framework that facilitates driving the efficiency assessments in line with individual preferences. Value-based DEA is a recent development that resorts to value assessment protocols from multiple criteria decision analysis (MCDA) to transform the original input/output data to a value scale. In this context, we introduce in this paper a piece-wise linear programming approach to value-based DEA, by employing a data transformation-variable alteration technique and assurance region constraints. We outline our approach by revisiting a previous efficiency assessment study drawn from the literature.
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来源期刊
International Journal of Multicriteria Decision Making
International Journal of Multicriteria Decision Making Business, Management and Accounting-Strategy and Management
CiteScore
0.70
自引率
0.00%
发文量
9
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
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