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A fuzzy DEMATEL – Fuzzy Binary Logistic Regression approach to evaluate and prioritize risks and simulated annealing optimization algorithm (an empirical study in energy projects)

Reyhane Hashemi (University of Science and Culture, Tehran, Iran)
Reza Kamranrad (Department of Industrial Engineering, Semnan University, Semnan, Iran)
Farnoosh Bagheri (University of Science and Culture, Tehran, Iran)
Iman Emami (Department of Change Management, Nardis Co., Tehran, Iran)

International Journal of Managing Projects in Business

ISSN: 1753-8378

Article publication date: 6 June 2020

Issue publication date: 22 June 2020

283

Abstract

Purpose

The aim of this paper is to predict and minimize the risks of oil, gas and petrochemical projects. Besides, reducing the likelihood of occurrence and minimizing risks impact on the projects to reduce the probable costs and improve the economic situation is another purpose of this paper.

Design/methodology/approach

This paper provides a fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) – a technique that assist to solve decision-making problems – and IP (Impact & Probability) table methods to identify and analyze critical risks in energy projects, and then fuzzy Binary Logistic Regression (BLR) in order to predict the probability of each level of risk for more efficient risk management in projects. Furthermore, in this paper, the fuzzy BLR (FBLR) is optimized such that the probability of a high level of risk for the implementation of the project has been minimized using meta-heuristic algorithm.

Findings

The results from the point of view of experts show that combination of fuzzy DEMATEL with FBLR approach as well as using SA algorithm, in order to optimize the high level of risks, can provide a smart approach to managing risks with more success.

Practical implications

The application of the proposed method is illustrated via a real data set from energy projects.

Originality/value

We propose combined fuzzy DEMATEL and FBLR methods to predict and optimize the risks of the energy projects, which is the innovation of this paper.

Keywords

Acknowledgements

Authors would like to thanks the anonymous experts who helped them to design the questionnaire and data gathering.

Citation

Hashemi, R., Kamranrad, R., Bagheri, F. and Emami, I. (2020), "A fuzzy DEMATEL – Fuzzy Binary Logistic Regression approach to evaluate and prioritize risks and simulated annealing optimization algorithm (an empirical study in energy projects)", International Journal of Managing Projects in Business, Vol. 13 No. 5, pp. 1025-1050. https://doi.org/10.1108/IJMPB-04-2019-0089

Publisher

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Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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