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Multiplicative data envelopment analysis cross-efficiency and stochastic weight space acceptability analysis for group decision making with interval multiplicative preference relations

机译:间隔乘法偏好关系组决策的乘法数据包络分析交叉效率和随机重量空间可接受性分析

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To deal with group decision making (GDM) with interval multiplicative preference relations (IMPRs), this paper proposes a novel method based on multiplicative data envelopment analysis (DEA) cross-efficiency and stochastic weight space acceptability analysis. We first develop a multiplicative DEA model to evaluate the relative efficiency of all alternatives of a given multiplicative preference relation (MPR). Then, we present a method, free from consistency adjustment, to derive a priority vector using the multiplicative DEA cross-efficiency with respect to the given MPR. For GDM with IMPRs, we consider the decision makers' weights as a uniform distribution for acceptability analysis. A modified unacceptability index is further defined to measure the unlikeliness for a particular alternative in a particular rank. Finally, we develop an assignment problem model to achieve an optimal ranking by minimizing the total rank unacceptability, and to compute the expected priority vector of all alternatives. Numerical examples are provided to show the applicability and justifications of the proposed GDM method. (C) 2019 Elsevier Inc. All rights reserved.
机译:为了处理间隔乘法偏好关系(IMP)的组决策(GDM),本文提出了一种基于乘法数据包络分析(DEA)交叉效率和随机重量空间可接受性分析的新方法。我们首先开发乘法DEA模型,以评估给定乘法偏好关系(MPR)的所有替代方案的相对效率。然后,我们介绍一种没有一致性调整的方法,以使用相对于给定MPR的乘法DEA交叉效率来推导优先级。对于GDM具有IMPS,我们将决策者的重量视为可接受性分析的统一分配。进一步定义了修改的不可接受性指标以测量特定等级中特定替代品的不核查。最后,我们开发了一个分配问题模型,以通过最小化总级别不可接受性来实现最佳排名,并计算所有替代方案的预期优先级向量。提供了数值示例以显示所提出的GDM方法的适用性和理由。 (c)2019 Elsevier Inc.保留所有权利。

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