scholarly journals Intuitionistic Fuzzy Hierarchical Multi-Criteria Decision Making for Evaluating Performances of Low-Carbon Tourism Scenic Spots

2020 ◽  
Vol 17 (17) ◽  
pp. 6259
Author(s):  
Xuan Yang ◽  
Zhou-Jing Wang
Keyword(s):  
Decision Making ◽  
Performance Evaluation ◽  
Pairwise Comparison ◽  
Evaluation Index System ◽  
Multi Criteria Decision Making ◽  
Low Carbon ◽  
Decision Matrix ◽  
Intuitionistic Fuzzy ◽  
Linguistic Term ◽  
Performance Evaluation Index

Low-carbon tourism is an effective solution to cope with the goal conflict between developing tourist economy and responding to carbon emission reduction and ecological environment protection. Tourism scenic spots are important carriers of tourist activities and play a crucial role in low-carbon tourism. There are multiple factors affecting the low-carbon performance of a tourism scenic spot, and thus the performance evaluation and ranking of low-carbon tourism scenic spots can be framed as a hierarchical multi-criteria decision making (MCDM) problem. This paper develops a novel method to tackle hierarchical MCDM problems, in which the importance preferences of criteria over the decision goal and sub-criteria with respect to the upper-level criterion are provided by linguistic-term-based pairwise comparisons and the assessments of alternatives over each of sub-criteria at the lowest level are furnished by positive interval values. The linguistic-term-based pairwise comparison matrices are converted into intuitionistic fuzzy preference relations and an approach is developed to obtain the global importance weights of the lowest level sub-criteria. A multiplicatively normalized intuitionistic fuzzy decision matrix is established from the interval-value-based assessments of alternatives and a method is proposed to determine the intuitionistic fuzzy value based comprehensive scores of alternatives. A case study is offered to illustrate how to build a performance evaluation index system of low-carbon tourism scenic spots located at Zhejiang Province of China and show the use of the proposed intuitionistic fuzzy hierarchical MCDM method.

Robust Benchmarking of Indian Mutual Funds-A Partial Frontier Approach

2015 ◽  
Vol 5 (2) ◽  
Author(s):  
Ram Pratap Sinha
Keyword(s):  
Decision Making ◽  
Performance Evaluation ◽  
Mutual Funds ◽  
Mutual Fund ◽  
Multi Criteria Decision Making ◽  
Risk Framework ◽  
Programming Techniques ◽  
Risk Free Rate ◽  
Risk Ratios ◽  
Free Rate

Performance analysis of mutual funds is usually made on the basis of return-risk framework. Traditionally, excess return (over risk-free rate) to risk ratios were used for the purpose mutual fund evaluation. Subsequently, the application of non-parametric mathematical programming techniques in the context of performance evaluation facilitated multi-criteria decision making. However,the estimates of performance on the basis of conventional programming techniques like DEA and FDH are affected by the presence of outliers in the sample observations. The present, accordingly uses more robust benchmarking techniques for evaluating the performance od sectoral mutual fund schemes based on observations for the second half of 2010. The USP of the present study is that it uses two partial frontier techniques (Order-m and Order- a) which are less susceptible to the problem of extreme data.

scholarly journals Fire Risk Assessment in Healthcare Settings: Application of FMEA Combined with Multi‐Criteria Decision Making Methods

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Fateme Omidvari ◽  
Mehdi Jahangiri ◽  
Reza Mehryar ◽  
Moslem Alimohammadlou ◽  
Mojtaba Kamalinia
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Fire Risk ◽  
Fire Detection ◽  
Healthcare Setting ◽  
Multi Criteria Decision Making ◽  
Intuitionistic Fuzzy ◽  
Healthcare Settings ◽  
Fire Risk Assessment ◽  
Risk Parameters

Fire is one of the most dangerous phenomena causing major casualties and financial losses in hospitals and healthcare settings. In order to prevent and control the fire sources, first risk assessment should be conducted. Failure Mode and Effect Analysis (FMEA) is one of the techniques widely used for risk assessment. However, Risk Priority Number (RPN) in this technique does not take into account the weight of the risk parameters. In addition, indirect relationships between risk parameters and expert opinions are not considered in decision making in this method. The aim is to conduct fire risk assessment of healthcare setting using the application of FMEA combined with Multi‐Criteria Decision Making (MCDM) methods. First, a review of previous studies on fire risk assessment was conducted and existing rules were identified. Then, the factors influencing fire risk were classified according to FMEA criteria. In the next step, weights of fire risk criteria and subcriteria were determined using Intuitionistic Fuzzy Multiplicative Best-Worst Method (IFMBWM) and different wards of the hospital were ranked using Interval-Valued Intuitionistic Fuzzy Combinative Distance-based Assessment (IVIFCODAS) method. Finally, a case study was performed in one of the hospitals of Shiraz University of Medical Sciences. In this study, fire alarm system (0.4995), electrical equipment and installations (0.277), and flammable materials (0.1065) had the highest weight, respectively. The hospital powerhouse also had the highest fire risk, due to the lack of fire extinguishers, alarms and fire detection, facilities located in the basement floor, boilers and explosive sensitivity, insufficient access, and housekeeping. The use of MCDM methods in combination with the FMEA method assesses the risk of fire in hospitals and health centers with great accuracy.

Multi-criteria decision-making based on hesitant fuzzy linguistic term sets: An outranking approach

2015 ◽  
Vol 86 ◽  
pp. 224-236 ◽  
Author(s):  
Jing Wang ◽  
Jian-qiang Wang ◽  
Hong-yu Zhang ◽  
Xiao-hong Chen
Keyword(s):  
Decision Making ◽  
Multi Criteria Decision Making ◽  
Linguistic Term ◽  
Fuzzy Linguistic
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