scholarly journals The Evaluation Method of Low-Carbon Scenic Spots by Combining IBWM with B-DST and VIKOR in Fuzzy Environment

2019 ◽  
Vol 17 (1) ◽  
pp. 89 ◽  
Author(s):  
Aijun Liu ◽  
Taoning Liu ◽  
Xiaohui Ji ◽  
Hui Lu ◽  
Feng Li
Keyword(s):  
Evaluation Method ◽  
Evaluation Criteria ◽  
Evaluation Process ◽  
Weighted Averaging ◽  
Low Carbon ◽  
Intuitionistic Fuzzy Numbers ◽  
Dempster Shafer Theory ◽  
Fuzzy Environment ◽  
Multicriteria Group Decision Making ◽  
Shafer Theory

With the concept of sustainability gaining popularity, low-carbon tourism has been widely considered. In this paper, a multicriteria group decision making (MCGDM) process based on an uncertain environment is proposed to study the evaluation problem of low-carbon scenic spots (LSSs). In order to minimize the influence of subjective and objective factors, the traditional Vlse Kriterjumska Optimizacija I Kompromisno Resenje (VIKOR) method is expanded, using the improved best and worst method (IBWM) and Bayes approximation method, based on Dempster-Shafer Theory (B-DST). First, in order to make the evaluation process more professional, a number of evaluation criteria are established as effective systems, followed by the use of triangular intuitionistic fuzzy numbers (TIFNs) to evaluate alternatives of LSSs. Next, according to the evaluation results, the weights of the criteria are determined by the IBWM method, and the weights of the expert panels (Eps) are determined by B-DST. Finally, a weighted averaging algorithm of TIFN is used to integrate the above results to expand the traditional VIKOR and obtain the optimal LSS. The applicability of this method is proven by example calculation. The main conclusions are as follows: tourist facilities and the eco-environment are the two most important factors influencing the choice of LSSs. Meanwhile, the roles of management and participant attitudes in LSS evaluations cannot be ignored.

scholarly journals Trapezoidal Intuitionistic Fuzzy Multiattribute Decision Making Method Based on Cumulative Prospect Theory and Dempster-Shafer Theory

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Xihua Li ◽  
Fuqiang Wang ◽  
Xiaohong Chen
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Value Function ◽  
Cumulative Prospect Theory ◽  
Intuitionistic Fuzzy Numbers ◽  
Attribute Weight ◽  
Intuitionistic Fuzzy ◽  
Dempster Shafer Theory ◽  
Fuzzy Environment ◽  
Shafer Theory

With respect to decision making problems under uncertainty, a trapezoidal intuitionistic fuzzy multiattribute decision making method based on cumulative prospect theory and Dempster-Shafer theory is developed. The proposed method reflects behavioral characteristics of decision makers, information fuzziness under uncertainty, and uncertain attribute weight information. Firstly, distance measurement and comparison rule of trapezoidal intuitionistic fuzzy numbers are used to derive value function under trapezoidal intuitionistic fuzzy environment. Secondly, the value function and decision weight function are used to calculate prospect values of attributes for each alternative. Then considering uncertain attribute weight information, Dempster-Shafer theory is used to aggregate prospect values for each alternative, and overall prospect values are obtained and thus the alternatives are sorted consequently. Finally, an illustrative example shows the feasibility of the proposed method.

scholarly journals Probability Estimation in the Framework of Intuitionistic Fuzzy Evidence Theory

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Yafei Song ◽  
Xiaodan Wang
Keyword(s):  
Evidence Theory ◽  
Estimation Method ◽  
Probability Estimation ◽  
Belief Functions ◽  
Intuitionistic Fuzzy ◽  
Dempster Shafer Theory ◽  
Fuzzy Environment ◽  
Shafer Theory ◽  
Theory Of Evidence ◽  
Interval Valued

Intuitionistic fuzzy (IF) evidence theory, as an extension of Dempster-Shafer theory of evidence to the intuitionistic fuzzy environment, is exploited to process imprecise and vague information. Since its inception, much interest has been concentrated on IF evidence theory. Many works on the belief functions in IF information systems have appeared. Although belief functions on the IF sets can deal with uncertainty and vagueness well, it is not convenient for decision making. This paper addresses the issue of probability estimation in the framework of IF evidence theory with the hope of making rational decision. Background knowledge about evidence theory, fuzzy set, and IF set is firstly reviewed, followed by introduction of IF evidence theory. Axiomatic properties of probability distribution are then proposed to assist our interpretation. Finally, probability estimations based on fuzzy and IF belief functions together with their proofs are presented. It is verified that the probability estimation method based on IF belief functions is also potentially applicable to classical evidence theory and fuzzy evidence theory. Moreover, IF belief functions can be combined in a convenient way once they are transformed to interval-valued possibilities.

LINGUISTIC AGGREGATION OPERATORS FOR LINGUISTIC DECISION MAKING BASED ON THE DEMPSTER-SHAFER THEORY OF EVIDENCE

2010 ◽  
Vol 18 (03) ◽  
pp. 287-304 ◽  
Author(s):  
J. M. MERIGÓ ◽  
M. CASANOVAS ◽  
L. MARTÍNEZ
Keyword(s):  
Decision Making ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
New Approach ◽  
Dempster Shafer Theory ◽  
Wide Range ◽  
Different Types ◽  
Linguistic Decision Making ◽  
Shafer Theory ◽  
Theory Of Evidence

In this paper, we develop a new approach for decision making with Dempster-Shafer theory of evidence by using linguistic information. We suggest the use of different types of linguistic aggregation operators in the model. We then obtain as a result, the belief structure — linguistic ordered weighted averaging (BS-LOWA), the BS — linguistic hybrid averaging (BS-LHA) and a wide range of particular cases. Some of their main properties are studied. Finally, we provide an illustrative example that shows the different results obtained by using different types of linguistic aggregation operators in the new approach.

scholarly journals Evaluation of Cloud Services: A Fuzzy Multicriteria Group Decision Making Method

2016 ◽  
Author(s):  
Santoso Wibowo ◽  
Hepu Deng ◽  
Wei Xu
Keyword(s):  
Decision Making ◽  
Performance Evaluation ◽  
Group Decision Making ◽  
Group Decision ◽  
Choquet Integral ◽  
Evaluation Process ◽  
Cloud Services ◽  
Intuitionistic Fuzzy Numbers ◽  
Decision Making Problem ◽  
Multicriteria Group Decision Making

This paper formulates the performance evaluation of cloud services as a multicriteria group decision making problem, and presents a fuzzy multicriteria group decision making method for evaluating the performance of cloud services. Interval-valued intuitionistic fuzzy numbers are used to model the inherent subjectiveness and imprecision of the performance evaluation process. An effective algorithm is developed based on the technique for order preference by similarity to ideal solution method and the Choquet integral operator for adequately solving the performance evaluation problem. An example is presented to demonstrate the applicability of the proposed fuzzy multicriteria group decision making method for solving the multicriteria group decision making problem in real world situations.

Benchmarking knowledge management practices in small and medium enterprises

2017 ◽  
Vol 24 (5) ◽  
pp. 1215-1233 ◽  
Author(s):  
Santoso Wibowo ◽  
Srimannarayana Grandhi
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Small And Medium Enterprises ◽  
Evaluation Criteria ◽  
Evaluation Process ◽  
Decision Makers ◽  
Content Type ◽  
Multicriteria Group Decision Making ◽  
Medium Enterprises

Purpose The purpose of this paper is to formulate the process of measuring and benchmarking the performance of knowledge management (KM) practices as a multicriteria group decision-making problem and present a new multicriteria group decision-making approach for effectively evaluating the performance of KM practices to meet the interests of various stakeholders in small and medium enterprises (SMEs). Design/methodology/approach A new multicriteria group decision-making approach is developed for evaluating the performance of KM practices of individual SMEs. Intuitionistic fuzzy numbers are used for representing the subjective assessments of decision makers in evaluating the relative importance of the evaluation criteria and the performance of individual KM practices with respect to specific evaluation criteria. A fuzzy multicriteria group decision-making algorithm is developed for measuring and benchmarking the performance of alternative KM practices. Findings The proposed multicriteria group decision-making approach is capable of effectively evaluating the performance of KM practices through adequately considering the presence of multiple decision makers, the multi-dimensional nature of the evaluation problem, and appropriately modeling the subjectiveness and imprecision of the evaluation process. The presentation of an example shows that the proposed fuzzy multicriteria group decision-making algorithm is simple to use and efficient in computation. Research limitations/implications The outcome of the multicriteria group decision-making approach is highly dependent on the inputs provided by the decision maker. Practical implications The novelty from this research lies in the utilization of a multicriteria group decision-making approach for evaluating the performance of KM practices in an organization. The outcome from the performance evaluation process allows the enterprise to adopt appropriate KM practices for achieving competitive advantages. Social implications The proposed multicriteria group decision-making approach has a significant social implication as it can be used as a decision-making tool for providing various decision makers in SMEs with useful and strategic information concerning the performance of KM practices in a given situation. Originality/value The originality of this paper lies in the development of the multicriteria group decision-making approach for effectively measuring and benchmarking the performance of KM practices of individual SMEs.

A DESCRIPTIVE DECISION-MAKING MODEL UNDER UNCERTAINTY: COMBINATION OF DEMPSTER-SHAFER THEORY AND PROSPECT THEORY

2013 ◽  
Vol 21 (01) ◽  
pp. 79-102 ◽  
Author(s):  
ELHUM NUSRAT ◽  
KOICHI YAMADA
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Real Life ◽  
Weighted Averaging ◽  
Dempster Shafer Theory ◽  
Decision Making Problem ◽  
Evidential Decision ◽  
Decision Weights ◽  
Shafer Theory ◽  
Decision Making Model

In this paper, a descriptive decision-making model under uncertainty is proposed which incorporates two types of decision attitudes for uncertainty; one is an attitude about ignorance (optimism/pessimism) and the other one is about risk (risk-seeking and risk-aversion). At first, Evidential Decision Making Problem (EDMP) has been defined where Dempster-Shafer Theory (DST) has been used to represent uncertainty. Then probability approximation approach of solving EDMP is shown. For deciding the decision weights in different attitudes of decision maker, Ordered Weighted Averaging (OWA) operator has been used. Later on, Prospect Theory has been applied to accomplish a descriptive decision-making model. To show the effectiveness of our approach, a real life decision problem of travelers' route choice from a set of alternatives has also been provided.

Robustness evaluation of coal mine based on FAHP and DST

2021 ◽  
pp. 1-9
Author(s):  
Xiaochuan Wang
Keyword(s):  
Quality Management ◽  
Coal Mine ◽  
Evaluation Method ◽  
Evaluation Model ◽  
Evaluation Index System ◽  
Analytic Hierarchy ◽  
Dempster Shafer Theory ◽  
Shafer Theory ◽  
Hierarchy Process ◽  
Error Proofing

Enterprise quality management robustness describes the effectiveness of quality management error-proofing system. In accordance with fuzzy analytic hierarchy process (FAHP) and Dempster-Shafer theory (DST), this research constructs the evaluation model of the quality management robustness of coal mine establishes the evaluation index system from seven aspects and three levels, and puts forward the evaluation method. At last, the effectiveness of the error-proofing system of coal mining enterprise is verified.

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