基于HTFWGBM算子的供应商选择模型研究
|
摘要
由于供应商选择中的的复杂性与不确定性以及人类认知的有限性,从而导致信息融合失真和决策结果不准确的情况。针对决策属性以犹豫三角模糊数(HTFN)给出的供应商的选择问题,本文提出一种基于HTFGWBM算子的决策算法。首先,针对犹豫三角模糊数和几何Bonferroni平均算子理论,分别定义了犹豫三角模糊几何Bonferroni平均(HTFGBM)算子和犹豫三角模糊几何加权Bonferroni平均(HTFGWBM)算子,同时分别研究了算子的幂等性,置换不变性,单调性和有界性等性质。其次,基于HTFGWBM算子构建新型犹豫多属性决策模型,结合HTFN排序方法进行备选供应商排序。最后通过算南水北调中线工程中的供应商选择实例证明了决策模型的可行性与有效性。结果表明,通过调整模型参数,模型具有一定的延展性和容错能力,能够很好的进行科学决策。
The complexity,uncertainty and limitation of human cognition in the processes of supplier selection lead to the distortion of information fusion and inaccuracy of decision-making.With respect of decision-making problems about supplier selection introduced by decision-making attributes and hesitate triangular fuzzy numbers(HTFN),a decision-making algorithm based on hesitate triangular fuzzy geometric weighted Bonferroni mean(HTFGWBM)operators is propased in this paper.First,in terms of hesitate triangular fuzzy numbers and geometric Bonferroni mean operator theory,HTFGWBM operators and hesitate triangular fuzzy geometric weighted Bonferroni mean(HTFGWBM)operator are defined respectively,and their constraints are explored,such as attributes of monotonic,limited and idempotent.Combining with HTFN sorting methods,then alternative suppliers based on the new hesitate multi-attribute decision-making model constructed with HTFGWBM operators are sequenced.Finally,a suppler selection example from an empirical project is illustrated to demonstrate the feasibility and effectiveness of the proposed decision-making model.The results show that this model is equipped with ductility and fault tolerance via the adjustment of parameters,which can be used in scientific decision-making.
The complexity,uncertainty and limitation of human cognition in the processes of supplier selection lead to the distortion of information fusion and inaccuracy of decision-making.With respect of decision-making problems about supplier selection introduced by decision-making attributes and hesitate triangular fuzzy numbers(HTFN),a decision-making algorithm based on hesitate triangular fuzzy geometric weighted Bonferroni mean(HTFGWBM)operators is propased in this paper.First,in terms of hesitate triangular fuzzy numbers and geometric Bonferroni mean operator theory,HTFGWBM operators and hesitate triangular fuzzy geometric weighted Bonferroni mean(HTFGWBM)operator are defined respectively,and their constraints are explored,such as attributes of monotonic,limited and idempotent.Combining with HTFN sorting methods,then alternative suppliers based on the new hesitate multi-attribute decision-making model constructed with HTFGWBM operators are sequenced.Finally,a suppler selection example from an empirical project is illustrated to demonstrate the feasibility and effectiveness of the proposed decision-making model.The results show that this model is equipped with ductility and fault tolerance via the adjustment of parameters,which can be used in scientific decision-making.
引文
[1]Atanassov K.Intuitionistic fuzzy sets[J].Fuzzy Sets and Systems,1986,20:87-96.
[2]Atanassov K,Gargov G.Interval-valued intuitionistic fuzzy sets[J].Fuzzy Sets and Systems,1989,31:343-349.
[3]Xu Zeshui,Yager R R.Intuitionistic and interval-valued intutionistic fuzzy preference relations and their measures of similarity for the evaluation of agreement within a group[J].Fuzzy Optimization Decision Making,2009,8(2):123-139.
[4]Shu Ming-huang,Cheng Ching-hsue,Chang Jingrong.Using intuitionistic fuzzy sets for fault tree analysis on printed circuit board assembly[J].Microelectronics Reliability,2006,46:2139-2148.
[5]Li Dengfeng.A ratio ranking method of triangular intuitionistic fuzzy numbers and its application to MADMproblems[J].Computers and Mathematics with Applications,2010,60(6):1557-1570.
[6]Wang Jianqiang,Zhang Zhong.Aggregation operators on intuitionistic trapezoidal fuzzy number and its application to multicriteria decision making problems[J].Journal of Systems Engineering and Electronics,2009,20(2):321-326.
[7]Wei Guiwu.Some arithmetic aggregation operators with intuitionistic trapezoidal fuzzy numbers and their application to group decision making[J].Journal of Computers,2010,5(3):345-351.
[8]Torra V,Narukawa Y.On hesitant fuzzy sets and decision[C]//Fuzzy Systems,the 18th IEEE International Conference,Jeju Island,Korea,August 20-24,2009:1378-1382.
[9]Torra V.Hesitant fuzzy sets[J].International Journal of In telligent Systems,2010,25:12-20.
[10]Chen Na,Xu Zeshui,Xia Meimei.Interval-valued hesitant preference relations and their applications to group decision making[J].Knowledge-Based Systems,2013,37:528-540.
[11]Chen Na,Xu Zeshui,Xia Meimei.Correlation coefficients of hesitant fuzzy sets and theirapplications to clustering analysis[J].Applied Mathematical Modeling,2013,37(4):2197-2211.
[12]Xia Meimei,Xu Zeshui.Hesitant fuzzy information aggregationin decision making[J].International Journal of Approximate Reasoning,2011,52(3):395-407.
[13]Xia Meimei,Xu Zeshui,Chen Na.Some hesitant fuzzy aggregation operators with their application in group decision making[J].Group Decision and Negotiation,2013,22(2):259-279.
[14]Wei Guiwu,Zhao Xiaofei,Lin Rui.Some hesitant interval-valued fuzzy aggregation operators and their applications to multiple attribute decision making[J].Knowledge-Based Systems,2013,46:43-53.
[15]Zhao Xiaofei,Lin Rui,Wei Guiwu.Hesitant triangular fuzzy information aggregation based on Einstein operations and their application to multiple attribute decision making[J].Expert Systems with Applications,2014,41(4):1086-1094.
[16]Xia Meimei,Xu Zeshui,Zhu Bin.Geometric Bonferroni means with their application in multi-criteria decision making[J].Knowledge-Based Systems,2013,40:88-100.
[17]Xu Zeshui.Fuzzy harmonic mean operators[J].International Journal of Intelligent Systems,2009,24(2),152-172.
[18]周晓辉,姚俭,吴天魁,等.三角模糊数直觉模糊Bonferroni平均算子及其应用[J].计算机应用研究,2015,32(2):434-438.
[19]周晓辉,姚俭,孙文浩,等.区间直觉模糊几何Bonferroni平均算子及其应用[J].计算机工程与应用,2016,52(3):12-16.
[20]梁邦龙,林杰,袁光辉.基于HTFWBM算子的多属性关联决策方法[J].科技管理研究,2016,52(23):244-248.
[21]Xu Zeshui,Yager R R.Some geometric aggregation operators based on intuitionistic fuzzy sets[J].International Journal of General Systems,2006,35(4):417-433.
[2]Atanassov K,Gargov G.Interval-valued intuitionistic fuzzy sets[J].Fuzzy Sets and Systems,1989,31:343-349.
[3]Xu Zeshui,Yager R R.Intuitionistic and interval-valued intutionistic fuzzy preference relations and their measures of similarity for the evaluation of agreement within a group[J].Fuzzy Optimization Decision Making,2009,8(2):123-139.
[4]Shu Ming-huang,Cheng Ching-hsue,Chang Jingrong.Using intuitionistic fuzzy sets for fault tree analysis on printed circuit board assembly[J].Microelectronics Reliability,2006,46:2139-2148.
[5]Li Dengfeng.A ratio ranking method of triangular intuitionistic fuzzy numbers and its application to MADMproblems[J].Computers and Mathematics with Applications,2010,60(6):1557-1570.
[6]Wang Jianqiang,Zhang Zhong.Aggregation operators on intuitionistic trapezoidal fuzzy number and its application to multicriteria decision making problems[J].Journal of Systems Engineering and Electronics,2009,20(2):321-326.
[7]Wei Guiwu.Some arithmetic aggregation operators with intuitionistic trapezoidal fuzzy numbers and their application to group decision making[J].Journal of Computers,2010,5(3):345-351.
[8]Torra V,Narukawa Y.On hesitant fuzzy sets and decision[C]//Fuzzy Systems,the 18th IEEE International Conference,Jeju Island,Korea,August 20-24,2009:1378-1382.
[9]Torra V.Hesitant fuzzy sets[J].International Journal of In telligent Systems,2010,25:12-20.
[10]Chen Na,Xu Zeshui,Xia Meimei.Interval-valued hesitant preference relations and their applications to group decision making[J].Knowledge-Based Systems,2013,37:528-540.
[11]Chen Na,Xu Zeshui,Xia Meimei.Correlation coefficients of hesitant fuzzy sets and theirapplications to clustering analysis[J].Applied Mathematical Modeling,2013,37(4):2197-2211.
[12]Xia Meimei,Xu Zeshui.Hesitant fuzzy information aggregationin decision making[J].International Journal of Approximate Reasoning,2011,52(3):395-407.
[13]Xia Meimei,Xu Zeshui,Chen Na.Some hesitant fuzzy aggregation operators with their application in group decision making[J].Group Decision and Negotiation,2013,22(2):259-279.
[14]Wei Guiwu,Zhao Xiaofei,Lin Rui.Some hesitant interval-valued fuzzy aggregation operators and their applications to multiple attribute decision making[J].Knowledge-Based Systems,2013,46:43-53.
[15]Zhao Xiaofei,Lin Rui,Wei Guiwu.Hesitant triangular fuzzy information aggregation based on Einstein operations and their application to multiple attribute decision making[J].Expert Systems with Applications,2014,41(4):1086-1094.
[16]Xia Meimei,Xu Zeshui,Zhu Bin.Geometric Bonferroni means with their application in multi-criteria decision making[J].Knowledge-Based Systems,2013,40:88-100.
[17]Xu Zeshui.Fuzzy harmonic mean operators[J].International Journal of Intelligent Systems,2009,24(2),152-172.
[18]周晓辉,姚俭,吴天魁,等.三角模糊数直觉模糊Bonferroni平均算子及其应用[J].计算机应用研究,2015,32(2):434-438.
[19]周晓辉,姚俭,孙文浩,等.区间直觉模糊几何Bonferroni平均算子及其应用[J].计算机工程与应用,2016,52(3):12-16.
[20]梁邦龙,林杰,袁光辉.基于HTFWBM算子的多属性关联决策方法[J].科技管理研究,2016,52(23):244-248.
[21]Xu Zeshui,Yager R R.Some geometric aggregation operators based on intuitionistic fuzzy sets[J].International Journal of General Systems,2006,35(4):417-433.