Improved TOPSIS Method Considering Fuzziness and Randomness in Multi-Attribute Group Decision Making

Cai, Mei; Hong, Yuanyuan

doi:10.3390/math10224200

Cited by 6 publications

(4 citation statements)

References 44 publications

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“…The ranking method of approximating ideal values (TOPSIS) is a multi-attribute decision analysis method. Its basic principle is to rank the evaluation object by detecting the distance between the object and the optimal solution and the worst solution, if the object is close to the optimal solution and far from the worst solution at the same time, it is the best; if it is the opposite, it is the worst [ 41 , 45 , 46 , 47 , 48 , 49 ]. By calculating the level value, the optimal solution, and the worst solution of community emergency management capability, calculating the distance between the level value with the optimal solution and the worst solution respectively, and finally comparing and ranking the evaluation results, the most likely evaluation result of community emergency management capability is determined.…”

Section: Community Emergency Management Capacity Evaluation Modelmentioning

confidence: 99%

Study on the Evaluation of Emergency Management Capacity of Resilient Communities by the AHP-TOPSIS Method

Wang

Deng

et al. 2022

IJERPH

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Community emergency management is directly related to the safety of people’s lives and properties and is concerned with economic development and social stability. This paper established an evaluation model of community emergency management capacity from the perspective of resilience based on hierarchical analysis (AHP) and distance between superior and inferior solutions (TOPSIS). In terms of infrastructure resilience, community organizational resilience, risk, and hidden danger management, emergency material security, emergency force construction, emergency literacy, and the evaluation index system of resilient community emergency management capacity were improved. By the AHP method, the weights of all indexes were determined scientifically. Combined with the TOPSIS method, the fit of the evaluated object which between the positive and negative ideal solution was calculated to determine the optimal evaluation among multiple experts. According to the validated assessment, the low-scoring indicators were analyzed to make practical suggestions for improvement. The results provide new theoretical methods and technical support for the assessment of community emergency response capacity, which also provides reference for the assessment of emergency response capacity in other fields.

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Section: Community Emergency Management Capacity Evaluation Modelmentioning

confidence: 99%

Study on the Evaluation of Emergency Management Capacity of Resilient Communities by the AHP-TOPSIS Method

Wang

Deng

et al. 2022

IJERPH

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“…The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a typical multi-attribute decision-making method [14,15]. For the object to be evaluated, two distances need to be calculated: one is the distance to the positive ideal solution (i.e., the optimal solution) and the other is the distance to the negative ideal solution (i.e., the worst solution).…”

Section: Introductionmentioning

confidence: 99%

Research on State Evaluation of Petrochemical Plants Based on Improved TOPSIS Method and Combined Weight

et al. 2023

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Due to the involvement of hazardous materials and the potential serious accidents that may occur in petrochemical plants, it is of great significance to develop real-time state evaluation methods offering high performance. Data-driven methods have received widespread attention following the development of advanced condition-monitoring systems. However, scarce training samples evaluated under multiple operating conditions are available because of the high stability and reliability requirements of petrochemical plants. In this paper, a real-time state evaluation method based on the technique for order preference by similarity to ideal solution (TOPSIS) is proposed, which circumvents dependence on data samples. First, the positive and negative ideal solutions of TOPSIS are determined using expert experience and the process index control limits of process cards. Then, fixed-value and fixed-interval indices are proposed to address the interval-optimal parameters. Subsequently, a new combined weight is established using the entropy method and the subjective weight coefficient. Finally, the above steps are integrated into an improved TOPSIS for the state evaluation of petrochemical plants. Experiments conducted on a fluid catalytic cracking (FCC) unit show that the proposed method can quantify the real-time operating status of a petrochemical plant. Furthermore, compared with the equal weight method, the evaluation result of combined weights is more aligned with the actual operating status.

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“…In the research in the field of decision making, aggregated fuzzy decision information in the form of cloud models to obtain decision results, and proposed a large-scale group classification decision method with dual trust-benefit factors in social networks. Cai et al (2022) proposed an asymmetric probabilistic linguistic cloud TOPSIS method. proposed a multi-stage decision making framework considering quantum-guided expert transfer based on a normal cloud model.…”

Section: Introductionmentioning

confidence: 99%

A cloud model-based probabilistic linguistic multi-attribute decision method and its application to public evacuation in nuclear accidents

Wang

Chen

2023

Preprint

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Probabilistic linguistic term set can effectively express the evaluation preferences of decision makers, and cloud model can combine fuzziness and randomness, describe the correlation between fuzziness and randomness with numerical features, and form a mutual mapping between qualitative and quantitative. For the multi-attribute decision problem with unknown expert weights and attribute weights under the probabilistic linguistic term set environment, this paper proposes a cloud model-based multi-attribute decision method. Firstly, golden section method is used to transform probabilistic linguistic information into digital features of clouds, and the definition of the probabilistic linguistic cloud and calculation formula of the distance between the probabilistic linguistic clouds are given. Secondly, the expert weights and attribute weights are calculated based on this distance formula, and the alternatives are ranked using the technique for order preference by similarity to ideal solution (TOPSIS). Finally, the proposed decision-making method is applied to the decision of public evacuation in nuclear accidents, and the feasibility of the proposed method is verified by comparative analysis.

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Improved TOPSIS Method Considering Fuzziness and Randomness in Multi-Attribute Group Decision Making

Cited by 6 publications

References 44 publications

Study on the Evaluation of Emergency Management Capacity of Resilient Communities by the AHP-TOPSIS Method

Study on the Evaluation of Emergency Management Capacity of Resilient Communities by the AHP-TOPSIS Method

Research on State Evaluation of Petrochemical Plants Based on Improved TOPSIS Method and Combined Weight

A cloud model-based probabilistic linguistic multi-attribute decision method and its application to public evacuation in nuclear accidents

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