A New Hybrid AHP and Dempster—Shafer Theory of Evidence Method for Project Risk Assessment Problem

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, a three-phase framework is proposed. In the first phase, quantitative research was conducted to identify the risk factors that can influence a project. Then, a hybrid PCA-agglomerative unsupervised machine learning algorithm is proposed to classify the projects in terms of Properties, Operational and Technological, Financial, and Strategic risk factors. In the third step, a hybrid AHP and Dempster—Shafer theory of evidence is presented to select the best alternative with the lowest level of overall risks. As a result, four groups of risk factors, including Properties, Operational and Technological, Financial, and Strategic risk factors, are considered. Afterward, using an L2^4 Taguchi method, several experiments with various dimensions have been designed which are then solved by the proposed algorithm. The outcomes are then analyzed using the Validating Index, Reduced Risk Indicator, and Solving Time. The findings indicated that, compared to 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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Development of a hybrid AHP and Dempster-Shafer theory of evidence for project risk assessment problem

Journal of Project Management ◽

10.5267/j.jpm.2021.10.003 ◽

2022 ◽

Vol 7 (2) ◽

pp. 77-94

Author(s):

Saad M. Albogami ◽

Mohd Khairol Anuar Bin Mohd Ariffin ◽

Eris Elianddy Bin Supeni ◽

Kamarul Arifin Ahmad

Keyword(s):

Risk Factors ◽

Risk Assessment ◽

Taguchi Method ◽

Risk Indicator ◽

Project Risk ◽

Strategic Risk ◽

Dempster Shafer Theory ◽

Shafer Theory ◽

Theory Of Evidence ◽

Reduced Risk

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 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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