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作 者:何杜博 黄栋[1] 石文成 HE Dubo;HUANG Dong;SHI Wencheng(Department of Management Engineering and Equipment Economic,Naval University of Engineering,Wuhan 430033,China;Department of Military Logistics,Army Logistics University,Chongqing 401331,China)
机构地区:[1]海军工程大学管理工程与装备经济系,湖北武汉430033 [2]陆军勤务学院军事物流系,重庆401331
出 处:《系统工程与电子技术》2021年第4期980-990,共11页Systems Engineering and Electronics
基 金:国家社会科学基金(19BGL291)资助课题。
摘 要:针对装备采购供应链的供应商准入评价中较少同时考虑主观判断模糊偏好及评价指标内在关联的问题,提出一种基于决策实验室分析法(decision making trial and evaluation laboratory,DEMATEL)与灰关联投影的混合多属性群决策模型,用以评价装备采购供应商质量绩效。该模型考虑了定量与定性融合的属性形式,将定性评价转化为直觉模糊数形式。首先,通过考虑专家偏好关联的λ模糊测度广义Shapley Choquet积分算子来集结主观群决策模糊信息。然后,拓展群组DEMATEL来确定模糊环境下的指标相关权重。最后,基于改进灰关联投影法集结主客观评价信息,得到供应商的优劣排序。通过实例对比及敏感性分析进一步表明模型的实用性较强、可操作性好,能有效解决混合多属性群决策问题。Aiming at the problem that the supplier access evaluation model in the early stage of the construction of the existing equipment procurement supply chain rarely considers the fuzzy preference of subjective judgment and the internal correlation of evaluation indicators,a mixed multi-attribute group decision model is proposed based on decision making trial and evaluation laboratory(DEMATEL)and gray correlation projection to evaluate the quality performance of equipment procurement suppliers.The model takes into account the combination of quantitative and qualitative attribute forms,and transforms the qualitative evaluation information into the form of intuitionistic fuzzy numbers.First,it aggregates the subjective group decision fuzzy information by considering the fuzzy measure generalized Shapley Choquet integral operator associated with expert preference.Then,the group DEMATEL method is extended to a fuzzy environment to determine the index weights with intrinsic associations.Finally,the improved grey association projection method is used to aggregate subjective and objective evaluation information to obtain the ranking of the final suppliers.The comparison of examples and sensitivity analysis show that the model has a strong practicability and a good operability,and can effectively solve the group decision problem under mixed attributes.
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