Objective:Existing research mainly relies on quantitative indicators.However,the subjectivity of qualitative indicators and the problem of their difficulty in quantification limit the comprehensiveness of evaluation.T...Objective:Existing research mainly relies on quantitative indicators.However,the subjectivity of qualitative indicators and the problem of their difficulty in quantification limit the comprehensiveness of evaluation.Therefore,a resilience supplier evaluation method based on the improved Z-number-ORESTE is proposed.Methods:Through the construction of a multi-tiered evaluation index system incorporating supplier capabilities,resources,strategic aspects,and resilience,Z-numbers are harnessed to signify qualitative indicators.An advanced Z-number distance metric is implemented,meticulously considering the impact exerted by the reliability portion of Z-numbers on information risk.The refined ORESTE ranking algorithm introduces the concepts of strong and weak orderings and capitalizes on the Borda assignment function.This approach facilitates a more precise appraisal of the performance of alternative solutions.By amalgamating the improved Z-number distance measurement approach with the ORESTE ranking methodology for multi-attribute decision-making,it becomes feasible to more efficiently assess the recovery capacities and adaptability of suppliers in the face of unforeseen incidents and risks.Results:Through the analysis of the comprehensive performance of the existing suppliers of a certain electronics enterprise,the results regarding the suppliers’recovery capabilities and adaptability when facing unexpected events and risks are obtained.Eventually,the suppliers that are in line with the long-term development strategy of the enterprise are selected.Conclusion:This evaluation system has verified its feasibility and effectiveness.Moreover,the system is capable of effectively identifying and selecting resilient suppliers,providing more reliable decision-making support for the enterprise’s supply chain management.展开更多
With the increasing utilization of liquefied natural gas(LNG)as a marine fuel,the safety and reliability of shore-based LNG bunkering operations have become vital concerns.Human factors are crucial to the successful e...With the increasing utilization of liquefied natural gas(LNG)as a marine fuel,the safety and reliability of shore-based LNG bunkering operations have become vital concerns.Human factors are crucial to the successful execution of these operations.However,predicting human reliability in such complex scenarios remains challenging.This paper focuses on the prediction of human reliability analysis(HRA)for shorebased LNG bunkering operations on tanker ships to address the aforementioned gap.Practical approaches to predicting HRA under the success likelihood index method(SLIM)and an improved Z-numbers approach are both adopted in this paper.SLIM provides a powerful tool to calculate human error,while the improved Z-numbers can address uncertainty and improve the reliability of qualitative expert judgments.Results show that the reliability of shore-based LNG bunkering operations is 0.861.In addition to its robust theoretical contribution,this research provides substantial practical contributions to LNG ship owners,ship superintendents,safety inspectors,and shore-based and ship crew for enhancing safety at the operational level and efficiency of shore-based LNG bunkering operations.展开更多
There are numerous studies about Z-numbers since its inception in 2011.Because Z-number concept reflects human ability to make rational decisions,Z-number based multi-criteria decision making problems are one of these...There are numerous studies about Z-numbers since its inception in 2011.Because Z-number concept reflects human ability to make rational decisions,Z-number based multi-criteria decision making problems are one of these studies.When the problem is translated from linguistic information into Z-number domain,the important question occurs that which Z-number should be selected.To answer this question,several ranking methods have been proposed.To compare the performances of these methods,benchmark set of fuzzy Z-numbers has been created in time.There are relatively new methods that their performances are not examined yet on this benchmark problem.In this paper,we worked on these studies which are relative entropy based Z-number ranking method and a method for ranking discrete Z-numbers.The authors tried to examine their performances on the benchmark problem and compared the results with the other ranking algorithms.The results are consistent with the literature,mostly.The advantages and the drawbacks of the methods are presented which can be useful for the researchers who are interested in this area.展开更多
针对任务风险难度量、评估信息不确定性强等问题,提出一种Z-number和改进DS证据理论的风险评估方法。利用Z-number方法描述评估指标,得到各风险等级的初始基本概率分配(basic probability assignment,BPA);基于信度熵和皮尔逊相关系数改...针对任务风险难度量、评估信息不确定性强等问题,提出一种Z-number和改进DS证据理论的风险评估方法。利用Z-number方法描述评估指标,得到各风险等级的初始基本概率分配(basic probability assignment,BPA);基于信度熵和皮尔逊相关系数改进DS证据理论克服悖论问题进行信息融合,确定风险的最终等级;接着,基于信息融合结果引入Joussleme距离求解专家可信度。最后,以重装空投任务为例,验证本文所提风险评估方法的合理性,并对比分析不同改进DS证据理论方法得到的结果,验证所提方法的有效性和准确性。展开更多
The primary goal of this research is to determine the optimal agricultural field selection that would most effectively support manufacturing producers in manufacturing production while accounting for unpredictability ...The primary goal of this research is to determine the optimal agricultural field selection that would most effectively support manufacturing producers in manufacturing production while accounting for unpredictability and reliability in their decision-making.The PFS is known to address the levels of participation and non-participation.To begin,we introduce the novel concept of a PFZN,which is a hybrid structure of Pythagorean fuzzy sets and the ZN.The PFZN is graded in terms of membership and non-membership,as well as reliability,which provides a strong advice in real-world decision support concerns.The PFZN is a useful tool for dealing with uncertainty in decision-aid problems.The PFZN is a practical way for dealing with such uncertainties in decision-aid problems.The list of aggregation operators:PFZN Einstein weighted averaging and PFZN Einstein weighted geometric,is established under the novel Pythagorean fuzzy ZNs.It is a more precise mathematical instrument for dealing with precision and uncertainty.The core of this research is to develop a numerical algorithmto tackle the uncertainty in real-life problems using PFZNs.To show the applicability and effectiveness of the proposed algorithm,we illustrate the numerical case study related to determining the optimal agricultural field.The main purpose of this work is to describe the extended EDAS approach,then compare the proposed methodology with many other methodologies now in use,and then demonstrate how the suggested methodology may be applied to real-world problems.In addition,the final ranking results that were obtained by the devised techniques weremore efficient and dependable in comparison to the results provided by other methods presented in the literature.展开更多
文摘Objective:Existing research mainly relies on quantitative indicators.However,the subjectivity of qualitative indicators and the problem of their difficulty in quantification limit the comprehensiveness of evaluation.Therefore,a resilience supplier evaluation method based on the improved Z-number-ORESTE is proposed.Methods:Through the construction of a multi-tiered evaluation index system incorporating supplier capabilities,resources,strategic aspects,and resilience,Z-numbers are harnessed to signify qualitative indicators.An advanced Z-number distance metric is implemented,meticulously considering the impact exerted by the reliability portion of Z-numbers on information risk.The refined ORESTE ranking algorithm introduces the concepts of strong and weak orderings and capitalizes on the Borda assignment function.This approach facilitates a more precise appraisal of the performance of alternative solutions.By amalgamating the improved Z-number distance measurement approach with the ORESTE ranking methodology for multi-attribute decision-making,it becomes feasible to more efficiently assess the recovery capacities and adaptability of suppliers in the face of unforeseen incidents and risks.Results:Through the analysis of the comprehensive performance of the existing suppliers of a certain electronics enterprise,the results regarding the suppliers’recovery capabilities and adaptability when facing unexpected events and risks are obtained.Eventually,the suppliers that are in line with the long-term development strategy of the enterprise are selected.Conclusion:This evaluation system has verified its feasibility and effectiveness.Moreover,the system is capable of effectively identifying and selecting resilient suppliers,providing more reliable decision-making support for the enterprise’s supply chain management.
文摘With the increasing utilization of liquefied natural gas(LNG)as a marine fuel,the safety and reliability of shore-based LNG bunkering operations have become vital concerns.Human factors are crucial to the successful execution of these operations.However,predicting human reliability in such complex scenarios remains challenging.This paper focuses on the prediction of human reliability analysis(HRA)for shorebased LNG bunkering operations on tanker ships to address the aforementioned gap.Practical approaches to predicting HRA under the success likelihood index method(SLIM)and an improved Z-numbers approach are both adopted in this paper.SLIM provides a powerful tool to calculate human error,while the improved Z-numbers can address uncertainty and improve the reliability of qualitative expert judgments.Results show that the reliability of shore-based LNG bunkering operations is 0.861.In addition to its robust theoretical contribution,this research provides substantial practical contributions to LNG ship owners,ship superintendents,safety inspectors,and shore-based and ship crew for enhancing safety at the operational level and efficiency of shore-based LNG bunkering operations.
文摘There are numerous studies about Z-numbers since its inception in 2011.Because Z-number concept reflects human ability to make rational decisions,Z-number based multi-criteria decision making problems are one of these studies.When the problem is translated from linguistic information into Z-number domain,the important question occurs that which Z-number should be selected.To answer this question,several ranking methods have been proposed.To compare the performances of these methods,benchmark set of fuzzy Z-numbers has been created in time.There are relatively new methods that their performances are not examined yet on this benchmark problem.In this paper,we worked on these studies which are relative entropy based Z-number ranking method and a method for ranking discrete Z-numbers.The authors tried to examine their performances on the benchmark problem and compared the results with the other ranking algorithms.The results are consistent with the literature,mostly.The advantages and the drawbacks of the methods are presented which can be useful for the researchers who are interested in this area.
文摘针对任务风险难度量、评估信息不确定性强等问题,提出一种Z-number和改进DS证据理论的风险评估方法。利用Z-number方法描述评估指标,得到各风险等级的初始基本概率分配(basic probability assignment,BPA);基于信度熵和皮尔逊相关系数改进DS证据理论克服悖论问题进行信息融合,确定风险的最终等级;接着,基于信息融合结果引入Joussleme距离求解专家可信度。最后,以重装空投任务为例,验证本文所提风险评估方法的合理性,并对比分析不同改进DS证据理论方法得到的结果,验证所提方法的有效性和准确性。
文摘The primary goal of this research is to determine the optimal agricultural field selection that would most effectively support manufacturing producers in manufacturing production while accounting for unpredictability and reliability in their decision-making.The PFS is known to address the levels of participation and non-participation.To begin,we introduce the novel concept of a PFZN,which is a hybrid structure of Pythagorean fuzzy sets and the ZN.The PFZN is graded in terms of membership and non-membership,as well as reliability,which provides a strong advice in real-world decision support concerns.The PFZN is a useful tool for dealing with uncertainty in decision-aid problems.The PFZN is a practical way for dealing with such uncertainties in decision-aid problems.The list of aggregation operators:PFZN Einstein weighted averaging and PFZN Einstein weighted geometric,is established under the novel Pythagorean fuzzy ZNs.It is a more precise mathematical instrument for dealing with precision and uncertainty.The core of this research is to develop a numerical algorithmto tackle the uncertainty in real-life problems using PFZNs.To show the applicability and effectiveness of the proposed algorithm,we illustrate the numerical case study related to determining the optimal agricultural field.The main purpose of this work is to describe the extended EDAS approach,then compare the proposed methodology with many other methodologies now in use,and then demonstrate how the suggested methodology may be applied to real-world problems.In addition,the final ranking results that were obtained by the devised techniques weremore efficient and dependable in comparison to the results provided by other methods presented in the literature.
