A method of minimizing rankings inconsistency is proposed for a decision-making problem with rankings of alternatives given by multiple decision makers according to multiple criteria. For each criteria, at first, the ...A method of minimizing rankings inconsistency is proposed for a decision-making problem with rankings of alternatives given by multiple decision makers according to multiple criteria. For each criteria, at first, the total inconsistency between the rankings of all alternatives for the group and the ones for every decision maker is defined after the decision maker weights in respect to the criteria are considered. Similarly, the total inconsistency between their final rankings for the group and the ones under every criteria is determined after the criteria weights are taken into account. Then two nonlinear integer programming models minimizing respectively the two total inconsistencies above are developed and then transformed to two dynamic programming models to obtain separately the rankings of all alternatives for the group with respect to each criteria and their final rankings. A supplier selection case illustrated the proposed method, and some discussions on the results verified its effectiveness. This work develops a new measurement of ordinal preferences’ inconsistency in multi-criteria group decision-making （MCGDM） and extends the cook-seiford social selection function to MCGDM considering weights of criteria and decision makers and can obtain unique ranking result.展开更多
A dynamic hesitant fuzzy linguistic group decisionmaking(DHFLGDM) problem is studied from the perspective of information reliability based on the theory of hesitant fuzzy linguistic term sets(HFLTSs). First, an approa...A dynamic hesitant fuzzy linguistic group decisionmaking(DHFLGDM) problem is studied from the perspective of information reliability based on the theory of hesitant fuzzy linguistic term sets(HFLTSs). First, an approach is applied to transform the dynamic HFLTSs(DHFLTSs) into a set of proportional linguistic terms to eliminate the time dimension. Second, expert reliability is measured by considering both group similarity and degree of certainty, and an optimization method is employed to quantify the linguistic terms by maximizing the group similarity. Third, through computing the attribute stability as well as its reliability, a combination rule which considers both reliability and weight is proposed to aggregate the information, and then the aggregated grade values and degree of stability are used to make a selection. Finally,the application and feasibility of the proposed method are verified through a case study and method comparison.展开更多
In emergency decision making(EDM),it is necessary to generate an effective alternative quickly.Case-based reasoning(CBR)has been applied to EDM;however,choosing the most suitable case from a set of similar cases after...In emergency decision making(EDM),it is necessary to generate an effective alternative quickly.Case-based reasoning(CBR)has been applied to EDM;however,choosing the most suitable case from a set of similar cases after case retrieval remains challenging.This study proposes a dynamic method based on case retrieval and group decision making(GDM),called dynamic casebased reasoning group decision making(CBRGDM),for emergency alternative generation.In the proposed method,first,similar historical cases are identified through case similarity measurement.Then,evaluation information provided by group decision makers for similar cases is aggregated based on regret theory,and comprehensive perceived utilities for the similar cases are obtained.Finally,the most suitable historical case is obtained from the case similarities and the comprehensive perceived utilities for similar historical cases.The method is then applied to an example of a gas explosion in a coal company in China.The results show that the proposed method is feasible and effective in EDM.The advantages of the proposed method are verified based on comparisons with existing methods.In particular,dynamic CBRGDM can adjust the emergency alternative according to changing emergencies.The results of application of dynamic CBRGDM to a gas explosion and comparison with existing methods verify its feasibility and practicability.展开更多
In the decision-making process,the decision information provided by decision makers over alter-natives may take the form of intuitionistic fuzzy numbers and come from different periods.The weight of information on dec...In the decision-making process,the decision information provided by decision makers over alter-natives may take the form of intuitionistic fuzzy numbers and come from different periods.The weight of information on decision makers,criteria,periods is usually completely unknown.To this issue,we first utilise hesitation degree information and introduce the concept of confi-dence degree function to determine the decision maker’s weights.Then we aggregate individual evaluation information into group evaluation information through intuitionistic fuzzy number weighted arithmetic averaging operator.We construct a nonlinear optimisation model to gain the criterion weights and apply the aggregate operator to gain the integrated rating value of alternatives in different periods,calculating the deviations of the integrated rating values with respect to their average.Then the period weights are been obtained by using the entropy method.According to the closeness coefficient between alternatives and ideal solution to sort the alternatives and select the optimal one.展开更多
基金supported by the National Natural Science Foundation of China (60904059 60975049)+1 种基金the Philosophy and Social Science Foundation of Hunan Province (2010YBA104)the National High Technology Research and Development Program of China (863 Program)(2009AA04Z107)
文摘A method of minimizing rankings inconsistency is proposed for a decision-making problem with rankings of alternatives given by multiple decision makers according to multiple criteria. For each criteria, at first, the total inconsistency between the rankings of all alternatives for the group and the ones for every decision maker is defined after the decision maker weights in respect to the criteria are considered. Similarly, the total inconsistency between their final rankings for the group and the ones under every criteria is determined after the criteria weights are taken into account. Then two nonlinear integer programming models minimizing respectively the two total inconsistencies above are developed and then transformed to two dynamic programming models to obtain separately the rankings of all alternatives for the group with respect to each criteria and their final rankings. A supplier selection case illustrated the proposed method, and some discussions on the results verified its effectiveness. This work develops a new measurement of ordinal preferences’ inconsistency in multi-criteria group decision-making （MCGDM） and extends the cook-seiford social selection function to MCGDM considering weights of criteria and decision makers and can obtain unique ranking result.
基金supported by the National Natural Science Foundation of China(71171112 71502073+2 种基金 71601002)the Scientific Innovation Research of College Graduates in Jiangsu Province(KYZZ150094)the Anhui Provincial Natural Science Foundation(1708085MG168)
文摘A dynamic hesitant fuzzy linguistic group decisionmaking(DHFLGDM) problem is studied from the perspective of information reliability based on the theory of hesitant fuzzy linguistic term sets(HFLTSs). First, an approach is applied to transform the dynamic HFLTSs(DHFLTSs) into a set of proportional linguistic terms to eliminate the time dimension. Second, expert reliability is measured by considering both group similarity and degree of certainty, and an optimization method is employed to quantify the linguistic terms by maximizing the group similarity. Third, through computing the attribute stability as well as its reliability, a combination rule which considers both reliability and weight is proposed to aggregate the information, and then the aggregated grade values and degree of stability are used to make a selection. Finally,the application and feasibility of the proposed method are verified through a case study and method comparison.
基金partly supported by the National Natural Science Foundation of China under the Grant Nos.71371053 and 71902034Humanities and Social Sciences Foundation of Chinese Ministry of Education,No.20YJC630229+1 种基金Humanities and Social Science Foundation of Fujian Province,No.FJ2019B079Science and Technology Development Center of Chinese Ministry of Education.No.2018A0I019.
文摘In emergency decision making(EDM),it is necessary to generate an effective alternative quickly.Case-based reasoning(CBR)has been applied to EDM;however,choosing the most suitable case from a set of similar cases after case retrieval remains challenging.This study proposes a dynamic method based on case retrieval and group decision making(GDM),called dynamic casebased reasoning group decision making(CBRGDM),for emergency alternative generation.In the proposed method,first,similar historical cases are identified through case similarity measurement.Then,evaluation information provided by group decision makers for similar cases is aggregated based on regret theory,and comprehensive perceived utilities for the similar cases are obtained.Finally,the most suitable historical case is obtained from the case similarities and the comprehensive perceived utilities for similar historical cases.The method is then applied to an example of a gas explosion in a coal company in China.The results show that the proposed method is feasible and effective in EDM.The advantages of the proposed method are verified based on comparisons with existing methods.In particular,dynamic CBRGDM can adjust the emergency alternative according to changing emergencies.The results of application of dynamic CBRGDM to a gas explosion and comparison with existing methods verify its feasibility and practicability.
基金supported by the Natural Science Foundation of China[grant number 71601059],[grant number 71673069].
文摘In the decision-making process,the decision information provided by decision makers over alter-natives may take the form of intuitionistic fuzzy numbers and come from different periods.The weight of information on decision makers,criteria,periods is usually completely unknown.To this issue,we first utilise hesitation degree information and introduce the concept of confi-dence degree function to determine the decision maker’s weights.Then we aggregate individual evaluation information into group evaluation information through intuitionistic fuzzy number weighted arithmetic averaging operator.We construct a nonlinear optimisation model to gain the criterion weights and apply the aggregate operator to gain the integrated rating value of alternatives in different periods,calculating the deviations of the integrated rating values with respect to their average.Then the period weights are been obtained by using the entropy method.According to the closeness coefficient between alternatives and ideal solution to sort the alternatives and select the optimal one.
文摘本文首先提出群区间直觉模糊有序加权几何(groupinterval-valuedintuitionistic fuzzy orderedweighted geometric,GIVIFOWG)算子和群区间直觉模糊有序加权平均(group interval-valued intuitionistic fuzzy ordered weighted averaging,GIVIFOWA)算子.利用GIVIFOWG算子或GIVIFOWA算子聚集群的决策矩阵以获得方案在属性上的综合区间直觉模糊决策矩阵(collectiveinterval-valuedintuitionistic fuzzy decision-matrix,CIVIFDM).然后定义了一个考虑犹豫度的区间直觉模糊熵(interval-valuedintuitionistic fuzzyentropy,IVIFE);通过熵衡量每个属性所含的信息来求解属性权重.最后,提出基于可能度的接近理想解的区间排序法(interval technique for order preference by similarity to an ideal solution,ITOPSIS)和区间得分函数法.在ITOPSIS法中,依据区间距离公式计算候选方案和理想方案的属性加权区间距离,进而采用ITOPSIS准则对各方案进行排序;在区间得分函数法中,算出CIVIFDM中各方案的得分值以及精确值,然后利用区间得分准则对各方案进行排序.实验结果验证了决策方法的有效性和可行性.
