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作 者:刘东海[1] 刘原园 陈晓红[2] LIU Dong-hai;LIU Yuan-yuan;CHEN Xiao-hong(Department of Statistics,H unan University of Science and Technology,Xiangtan 411201,China;Mobile E--business ColIaborative Innovation Center of Hunan Province,Hunan University of Commerce,Changsha 410205,China)
机构地区:[1]湖南科技大学应用统计系,湖南湘潭411201 [2]湖南商学院湖南省移动电子商务协同创新中心,湖南长沙410205
出 处:《中国管理科学》2019年第1期174-183,共10页Chinese Journal of Management Science
基 金:国家自然科学基金重点资助项目(714310006);国家自然科学青年基金项目(11501191);湖南省自然科学基金资助项目(2017JJ2096);国家社科基金资助项目(15BTJ028)
摘 要:在犹豫直觉模糊语言集和语言尺度函数的基础上定义了均值-标准差偏好的Hamming距离,并提出了基于犹豫直觉模糊语言集距离TOPSIS和TODIM的多属性决策方法,进一步利用这两种方法对实例问题建筑商的招标方案进行排序,并讨论了偏好参数对排序结果的灵敏度分析。为验证上述方法的有效性,与已有方法对同一实例的排序结果进行了比较分析。In many multi-criteria decision making(MCDM)problems,due to the complexity and fuzziness of the decision making environment,many attributes should be assessed in a quantitative form.In this case,decision makers can’t just use single-value linguistic term to express their preferences because they are hesitant with decision information,they often provide the hesitant intuitionistic fuzzy linguistic term set to depict the decision information.As far as we know,existing studies often used the subscript of linguistic terms directly in the process of operations,which can’t consider the semantic environment.This may cause information distortion,but the linguistic scale function can solve this problem.Therefore,the Hamming distance of mean-standard deviation with preference between hesitant intuitionistic fuzzy linguistic term set based on linguistic scale function is defined,the related properties are also proved.Then the multiple attribute decision making method of TOPSIS and TODIM is proposed.These two methods can solve the ranking of alternatives effectively in multiple attribute decision making problems.Furthermore,in order to illustrate the feasibility and effectiveness,the same numerical example concerning construction company bidding schemes are sorted by using these two methods.Finally,the sensitivity analysis of the preference parameters on the ranking result and comparision analysis with other method are also discussed.
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