This paper is to provide a novel approach for the spatial aggregation of judgment matrices.The optimal aggregation method of judgment matrices based on spatial Steiner-Weber point can effectively aggregate the prefere...This paper is to provide a novel approach for the spatial aggregation of judgment matrices.The optimal aggregation method of judgment matrices based on spatial Steiner-Weber point can effectively aggregate the preference information of group members and achieve the optimization of group preference.The method comprises three key elements:The spatial mapping of the judgment matrices,the spatial optimal aggregation model of the judgment matrices,and the plant growth simulation algorithm(PGSA)is used to find the optimal aggregation points.Firstly,the judgment matrices are mapped into a set of spatial multidimensional coordinates by using spatial mapping rules.Secondly,the spatial Steiner-Weber point is used as the prototype to construct the spatial aggregation model.Thirdly,the PGSA algorithm is used to find the spatial aggregation points,whose spatial weighted Euclidean distance to all the decision makers’preference points is minimal.The optimal aggregation matrix is composed of these optimal aggregation points,which can accurately reflect the decision maker's comprehensive opinions.Finally,the effectiveness and rationality of this method are verified by comparing with the classical group preference aggregation methods.展开更多
This paper proposes anoptimal fuzzy-based model for obtaining crisp priorities for Fuzzy-AHP comparison matrices.Crisp judgments cannot be given for real-life situations,as most of these include some level of fuzzines...This paper proposes anoptimal fuzzy-based model for obtaining crisp priorities for Fuzzy-AHP comparison matrices.Crisp judgments cannot be given for real-life situations,as most of these include some level of fuzziness and com-plexity.In these situations,judgments are represented by the set of fuzzy numbers.Most of the fuzzy optimization models derive crisp priorities for judgments repre-sented with Triangular Fuzzy Numbers(TFNs)only.They do not work for other types of Triangular Shaped Fuzzy Numbers(TSFNs)and Trapezoidal Fuzzy Numbers(TrFNs).To overcome this problem,a sum of squared error(SSE)based optimization model is proposed.Unlike some other methods,the proposed model derives crisp weights from all of the above-mentioned fuzzy judgments.A fuzzy number is simulated using the Monte Carlo method.A threshold-based constraint is also applied to minimize the deviation from the initial judgments.Genetic Algorithm(GA)is used to solve the optimization model.We have also conducted casestudiesto show the proposed approach’s advantages over the existingmethods.Results show that the proposed model outperforms other models to minimize SSE and deviation from initial judgments.Thus,the proposed model can be applied in various real time scenarios as it can reduce the SSE value upto 29%compared to the existing studies.展开更多
为合理评价管制员综合素质,保障空管运行安全,提出了一种将群决策、区间数和层次分析法相结合的综合评价方法。基于少数服从多数的原则,给出群决策中专家系数的计算方法,提出两个关于区间数和区间数判断矩阵(Interval Number Judgement ...为合理评价管制员综合素质,保障空管运行安全,提出了一种将群决策、区间数和层次分析法相结合的综合评价方法。基于少数服从多数的原则,给出群决策中专家系数的计算方法,提出两个关于区间数和区间数判断矩阵(Interval Number Judgement Matrix,INJM)的定理并进行了证明,基于区间数理论,给出了一种构造具有一致性判断矩阵的方法,随后给出了评价指标权重的计算方法,最终建立了管制员综合素质评价模型。结果表明,指令准确性、航空器调配合理性、冲突与特情处置能力、听力和团队合作5个因素对管制员综合素质起着主要作用,可为管制员的培养、选拔、测评和培训提供参考。展开更多
基金partially supported by the National Natural Science Foundation of China under Grant No.71871106the Fundamental Research Funds for the Central Universities under Grant Nos. JUSRP1809ZD,2019JDZD06, JUSRP321016+5 种基金sponsored by the Major Projects of Educational Science Fund of Jiangsu Province in 13th Five-Year Plan under Grant No. A/2016/01the Key Project of Philosophy and Social Science Research in Universities of Jiangsu Province under Grant No. 2018SJZDI051the Major Projects of Philosophy and Social Science Research of Guizhou Province under Grant No. 21GZZB32Project of Chinese Academic Degrees and Graduate Education under Grant No. 2020ZDB2Major research project of the 14th Five-Year Plan for Higher Education Scientific Research of Jiangsu Higher Education Association under Grant No. ZDGG02the Henan University of Technology High-level Talents Scientific Research Fund (2022BS043)
文摘This paper is to provide a novel approach for the spatial aggregation of judgment matrices.The optimal aggregation method of judgment matrices based on spatial Steiner-Weber point can effectively aggregate the preference information of group members and achieve the optimization of group preference.The method comprises three key elements:The spatial mapping of the judgment matrices,the spatial optimal aggregation model of the judgment matrices,and the plant growth simulation algorithm(PGSA)is used to find the optimal aggregation points.Firstly,the judgment matrices are mapped into a set of spatial multidimensional coordinates by using spatial mapping rules.Secondly,the spatial Steiner-Weber point is used as the prototype to construct the spatial aggregation model.Thirdly,the PGSA algorithm is used to find the spatial aggregation points,whose spatial weighted Euclidean distance to all the decision makers’preference points is minimal.The optimal aggregation matrix is composed of these optimal aggregation points,which can accurately reflect the decision maker's comprehensive opinions.Finally,the effectiveness and rationality of this method are verified by comparing with the classical group preference aggregation methods.
文摘This paper proposes anoptimal fuzzy-based model for obtaining crisp priorities for Fuzzy-AHP comparison matrices.Crisp judgments cannot be given for real-life situations,as most of these include some level of fuzziness and com-plexity.In these situations,judgments are represented by the set of fuzzy numbers.Most of the fuzzy optimization models derive crisp priorities for judgments repre-sented with Triangular Fuzzy Numbers(TFNs)only.They do not work for other types of Triangular Shaped Fuzzy Numbers(TSFNs)and Trapezoidal Fuzzy Numbers(TrFNs).To overcome this problem,a sum of squared error(SSE)based optimization model is proposed.Unlike some other methods,the proposed model derives crisp weights from all of the above-mentioned fuzzy judgments.A fuzzy number is simulated using the Monte Carlo method.A threshold-based constraint is also applied to minimize the deviation from the initial judgments.Genetic Algorithm(GA)is used to solve the optimization model.We have also conducted casestudiesto show the proposed approach’s advantages over the existingmethods.Results show that the proposed model outperforms other models to minimize SSE and deviation from initial judgments.Thus,the proposed model can be applied in various real time scenarios as it can reduce the SSE value upto 29%compared to the existing studies.
文摘为合理评价管制员综合素质,保障空管运行安全,提出了一种将群决策、区间数和层次分析法相结合的综合评价方法。基于少数服从多数的原则,给出群决策中专家系数的计算方法,提出两个关于区间数和区间数判断矩阵(Interval Number Judgement Matrix,INJM)的定理并进行了证明,基于区间数理论,给出了一种构造具有一致性判断矩阵的方法,随后给出了评价指标权重的计算方法,最终建立了管制员综合素质评价模型。结果表明,指令准确性、航空器调配合理性、冲突与特情处置能力、听力和团队合作5个因素对管制员综合素质起着主要作用,可为管制员的培养、选拔、测评和培训提供参考。
