基于模糊语言偏好的工程监理信用评价  

Supervision Engineers Credit Evaluation Based on Fuzzy Linguistic Preference

作　　者：赵丽丽[1] 王雪青[1] 陈超 陈杨杨[3] 

机构地区：[1]天津大学管理与经济学部,天津300072 [2]天津地铁资源投资有限公司发展策划部,天津300102 [3]天津城建大学经济与管理学院,天津300384

出　　处：《模糊系统与数学》2015年第3期154-160,共7页Fuzzy Systems and Mathematics

基　　金：国家自然科学基金资助项目(71172148);住房和城乡建设部基金资助项目(2011-R3-18)

摘　　要：传统信用评价方法多从单一建筑市场主体的视角对工程监理进行信用评价,且由于外界信息的不确定性和评价主体的主观偏好,往往使得评价结果失真。针对此本文从利益相关者的视角,在二元语义评价集的基础上引入上下文无关语法对工程监理信用进行评价,此方法将由上下文无关语法表示的语言评价集转换为语言区间值形式,并通过二元语义相关算子求得众多利益相关者的集结模糊偏好矩阵,最后运用偏好度公式与非优势度公式对工程监理信用水平进行排序。算例分析表明该方法可以减少模糊语言评价信息集结和运算过程中出现的信息损失和信息扭曲。Traditional credit evaluation methods only evaluate the credit of the supervision engineers from the perspective of a single subject. Even because the supervision engineers＇ information is uncertain and evaluation subjects are inherently subjective, it will lead evaluation information can＇t be accurately expressed with precise real number. Therefore, from the stakeholders＇ perspective, Context-free grammar based on 2-tuple linguistic are lead up to evaluate comprehensively the credit of supervision engineers. This method converts the linguistic evaluate sets represented by context-free grammar to the forms of linguistic interval-valued. Then aggregation fuzzy preference matrix of the stakeholders is obtained by 2-tuple linguistic related operators. Finally, rank the supervision engineers according to the preference degree equation and the non-dominance degree equation. The numerical example shows that the method can effectively avoid the loss and distortion of information in the process of fuzzy linguistic assessment information gathering and operating.

关 键 词：模糊语言偏好 二元语义 上下文无关语法 利益相关者 信用评价 

分 类 号：TU711[建筑科学—建筑技术科学]