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A multi-objective optimization approach for selecting risk response actions: considering environmental and secondary risks

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  • Mahsa Parsaei Motamed

    (Islamic Azad University, South Tehran Branch)

  • Shahrooz Bamdad

    (Islamic Azad University, South Tehran Branch)

Abstract

Given the intense competition and the current economic and political situation, it is clear that the execution projects, especially the large ones, will face many risks, which would be irreparable if not identified, analyzed, and responded to, so the risk management role is very effective in this regard. On the other hand, despite the available research, there are still significant shortcomings, especially in the risk response phase. It can be said that finding the best set of risk response actions is the main prerequisite for the success of the risk management process. One of the problems is the lack of focus of most of the existing approaches on secondary risks, which may arise during the implementation of the selected risk response actions. Therefore, to improve the selection of appropriate risk response actions, this study provides a goal programming model concerning secondary risks and intending to minimize undesirable deviations from expected changes in cost, time, and quality of the project due to the risk occurrence. After solving this model, an optimal set of both primary and secondary response actions is selected. A case study on the environmental risks of an oil and gas project has been conducted to demonstrate the model’s efficiency.

Suggested Citation

  • Mahsa Parsaei Motamed & Shahrooz Bamdad, 2022. "A multi-objective optimization approach for selecting risk response actions: considering environmental and secondary risks," OPSEARCH, Springer;Operational Research Society of India, vol. 59(1), pages 266-303, March.
    • Handle: RePEc:spr:opsear:v:59:y:2022:i:1:d:10.1007_s12597-021-00541-5
    DOI: 10.1007/s12597-021-00541-5
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    References listed on IDEAS

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    1. Edouard Kujawski, 2002. "Selection of technical risk responses for efficient contingencies," Systems Engineering, John Wiley & Sons, vol. 5(3), pages 194-212.
    2. A. Charnes & W. W. Cooper, 1963. "Programming with linear fractional functionals," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 10(1), pages 273-274, March.
    3. I Ben-David & T Raz, 2001. "An integrated approach for risk response development in project planning," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(1), pages 14-25, January.
    4. Zhang, Yao & Zuo, Fei & Guan, Xin, 2020. "Integrating case-based analysis and fuzzy optimization for selecting project risk response actions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    5. Seyed Mohammad Seyedhoseini & Siamak Noori & Mohammad Ali Hatefi, 2009. "An Integrated Methodology for Assessment and Selection of the Project Risk Response Actions," Risk Analysis, John Wiley & Sons, vol. 29(5), pages 752-763, May.
    6. Zafra-Cabeza, Ascensión & Ridao, Miguel A. & Camacho, Eduardo F., 2008. "Using a risk-based approach to project scheduling: A case illustration from semiconductor manufacturing," European Journal of Operational Research, Elsevier, vol. 190(3), pages 708-723, November.
    7. Mohammad Ali Hatefi & Seyed Mohammad Seyedhoseini, 2012. "Comparative Review on the Tools and Techniques for Assessment and Selection of the Project Risk Response Actions (RRA)," International Journal of Information Technology Project Management (IJITPM), IGI Global, vol. 3(3), pages 60-78, July.
    8. Nguyen, Trong-Hung & Marmier, François & Gourc, Didier, 2013. "A decision-making tool to maximize chances of meeting project commitments," International Journal of Production Economics, Elsevier, vol. 142(2), pages 214-224.
    9. KIlIç, Murat & Ulusoy, Gündüz & Serifoglu, Funda Sivrikaya, 2008. "A bi-objective genetic algorithm approach to risk mitigation in project scheduling," International Journal of Production Economics, Elsevier, vol. 112(1), pages 202-216, March.
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    Cited by:

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