Uncertainty Modeling in Risk Assessment Based on Dempster–Shafer Theory of Evidence with Generalized Fuzzy Focal Elements

In this paper, a new hybrid AHP and Dempster-Shafer Theory of Evidence is presented for solving the problem of choosing the best project among a list of available alternatives while uncertain risk factors are taken into account. The aim is to minimize overall risks. For this purpose, four groups of risk factors, including Properties, Operational and Technological, Financial, Strategic risk factors, are considered. Then using an L24 Taguchi method, several experiments with various dimensions have been designed and solved by the proposed algorithm. The outcomes are then analyzed using the Validating Index (VI), Reduced Risk Indicator (R.R.I%), and Solving time. The findings indicated that, compared to the classic AHP, the results of the proposed hybrid method were different in most cases due to uncertainty of risk factors. It was observed that the method could be safely used for selecting project problems in real industries.

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An Evidential Model for Environmental Risk Assessment in Projects Using Dempster–Shafer Theory of Evidence

Sustainability ◽

10.3390/su11226329 ◽

2019 ◽

Vol 11 (22) ◽

pp. 6329 ◽

Cited By ~ 3

Author(s):

Hatefi ◽

Basiri ◽

Tamošaitienė

Keyword(s):

Risk Assessment ◽

Sustainable Development ◽

Environmental Risk ◽

Environmental Risk Assessment ◽

Fuzzy Inference ◽

Inference System ◽

Dempster Shafer Theory ◽

Proposed Model ◽

Shafer Theory ◽

Theory Of Evidence

One of the goals of sustainable development is to achieve economic and social growth according to environmental criteria. Nowadays, impact assessment is an efficient decision making method in planning and management with environmental perspectives. Environmental risk assessment is a tool to reduce the impacts and consequences of various activities on the environment in order to achieve sustainable development. One of the commonly used environmental risk assessment methods is the probability–impact matrix method, which is known as a quantitative method for risk assessment of projects. In this method, numerical estimates of probability and impact of risk occurrence are very difficult, and these factors are associated with uncertainty. When uncertainty exists, data integration is of great importance, for which the fuzzy inference system and evidence theory are known as effective methods. Unavailability of experts’ opinion and the exponential growth of the number of required fuzzy rules associated with the risk factors are two drawbacks of fuzzy inference. Dempster–Shafer’s theory of evidence is one of the popular theories used in intelligent systems for modeling and reasoning under uncertainty and inaccuracy. In this paper, an evidential model for project environmental risk assessment is proposed based on the Dempster–Shafer theory, which is capable of taking into account the uncertainties. The proposed model is used to assess the environmental risks of Maroon oil pipelines in Isfahan. In addition, the proposed model is used in the case of tunneling risk assessment taken from the subject literature. To evaluate the validity of the proposed evidential model, the results are compared in two case studies, with the results of the conventional risk assessment method and the fuzzy inference system method. The comparative results show that the proposed model has a high potential for project risk assessment under an uncertain environment.

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An Improved Algorithm for Dempster-Shafer Theory of Evidence

2009 International Conference on Electronic Commerce and Business Intelligence ◽

10.1109/ecbi.2009.44 ◽

2009 ◽

Cited By ~ 3

Author(s):

Yan Chenghua ◽

Chen Qixiang

Keyword(s):

Dempster Shafer Theory ◽

Shafer Theory ◽

Theory Of Evidence ◽

Improved Algorithm

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Maintenance policy performance assessment in presence of imprecision based on Dempster–Shafer Theory of Evidence

Information Sciences ◽

10.1016/j.ins.2012.11.003 ◽

2013 ◽

Vol 245 ◽

pp. 112-131 ◽

Cited By ~ 30

Author(s):

P. Baraldi ◽

M. Compare ◽

E. Zio

Keyword(s):

Performance Assessment ◽

Maintenance Policy ◽

Policy Performance ◽

Dempster Shafer Theory ◽

Shafer Theory ◽

Theory Of Evidence

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A MODIFIED D NUMBERS METHODOLOGY FOR ENVIRONMENTAL IMPACT ASSESSMENT

Technological and Economic Development of Economy ◽

10.3846/20294913.2016.1216018 ◽

2017 ◽

Vol 24 (2) ◽

pp. 653-669 ◽

Cited By ~ 10

Author(s):

Ningkui WANG ◽

Daijun WEI

Keyword(s):

Environmental Impact ◽

Impact Assessment ◽

Environmental Impact Assessment ◽

Previous Method ◽

Combination Process ◽

Dempster Shafer Theory ◽

Shafer Theory ◽

Theory Of Evidence ◽

D Numbers ◽

Commutative Property

Environmental impact assessment (EIA) is usually evaluated by many factors influenced by various kinds of uncertainty or fuzziness. As a result, the key issues of EIA problem are to represent and deal with the uncertain or fuzzy information. D numbers theory, as the extension of Dempster-Shafer theory of evidence, is a desirable tool that can express uncertainty and fuzziness, both complete and incomplete, quantitative or qualitative. However, some shortcomings do exist in D numbers combination process, the commutative property is not well considered when multiple D numbers are combined. Though some attempts have made to solve this problem, the previous method is not appropriate and convenience as more information about the given evaluations represented by D numbers are needed. In this paper, a data-driven D numbers combination rule is proposed, commutative property is well considered in the proposed method. In the combination process, there does not require any new information except the original D numbers. An illustrative example is provided to demonstrate the effectiveness of the method.

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