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Group heterogeneity in multi member decision making model with an application to warehouse location selection in a supply chain

机译:多成员决策模型中的组异质性及其在供应链中仓库位置选择中的应用

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摘要

Group decision making (GDM) is more effective in extracting the real case scenarios of the decision problems to add competitive advantages in a supply chain. Group members from wider spectrum of the environment naturally command variation in knowledge level to their respective domain. The degree of heterogeneity of the decision makers in a group plays a crucial role in realistic assessment of both alternatives and selection criteria. This paper proposes a new Multi criteria GDM approach in adroit exploitation of the group heterogeneity during evaluation process and restrict the biasness of information while decision making. The importance of the heterogeneous degree of expertise is established through pair wise preference comparison matrix. To overcome the biasness, the consistency check mechanism of analytical hierarchy process (AHP) is employed. A real case example on warehouse location selection in a supply chain is illustrated to demonstrate the validity and effectiveness of the proposed approach. In order to ensure the applicability, compatibility and validity of the proposed approach, comparative study is carried out with the proven and established MCDM methodologies SAW, MOORA, TOPSIS, VIKOR, ELECTRE Ⅱ, COPRAS and PROMETHEE. ANOVA, Sensitivity analysis (SA) and other investigations find the proposed approach as a rational, robust, effective and precise decision making aid to the supply chain managers.
机译:团体决策(GDM)在提取决策问题的实际案例以增加供应链中的竞争优势时更为有效。来自更广泛环境的小组成员自然会要求知识水平在各自领域内变化。群体中决策者的异质程度在现实评估替代方案和选择标准中起着至关重要的作用。本文提出了一种新的多准则GDM方法,用于在评估过程中充分利用群体异质性,并在决策时限制信息的偏差。通过成对的偏好比较矩阵可以确定专业知识异质程度的重要性。为了克服偏差,采用了层次分析法(AHP)的一致性检查机制。以供应链中仓库位置选择为例,说明了该方法的有效性和有效性。为了确保所提方法的适用性,兼容性和有效性,对已证明和建立的MCDM方法SAW,MOORA,TOPSIS,VIKOR,ELECTREⅡ,COPRAS和PROMETHEE进行了比较研究。方差分析,敏感性分析(SA)和其他调查发现,所提出的方法是对供应链管理者的合理,稳健,有效和精确的决策帮助。

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