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A Markov Chain Approach to Multicriteria Decision Analysis with an Application to Offshore Decommissioning

Author

Listed:
  • Fernanda F. Moraes

    (Alberto Luiz Coimbra Institute for Graduate School and Research in Engineering, Federal University of Rio de Janeiro, Rio de Janeiro 21941-598, Brazil)

  • Virgílio José M. Ferreira Filho

    (Alberto Luiz Coimbra Institute for Graduate School and Research in Engineering, Federal University of Rio de Janeiro, Rio de Janeiro 21941-598, Brazil)

  • Carlos Eduardo Durange de C. Infante

    (Alberto Luiz Coimbra Institute for Graduate School and Research in Engineering, Federal University of Rio de Janeiro, Rio de Janeiro 21941-598, Brazil
    Department of Business and Accounting Sciences, Universidade Federal de São João del Rei, São João del Rei 36307-352, Brazil)

  • Luan Santos

    (Alberto Luiz Coimbra Institute for Graduate School and Research in Engineering, Federal University of Rio de Janeiro, Rio de Janeiro 21941-598, Brazil
    Faculty of Business and Accounting Sciences, Federal University of Rio de Janeiro, Rio de Janeiro 22290-240, Brazil)

  • Edilson F. Arruda

    (Alberto Luiz Coimbra Institute for Graduate School and Research in Engineering, Federal University of Rio de Janeiro, Rio de Janeiro 21941-598, Brazil
    Department of Decision Analytics and Risk, Southampton Business School, University of Sohtampton, 12 University Rd., Highfield, Southampton SO17 1BJ, UK)

Abstract

This paper proposes a novel approach that makes use of continuous-time Markov chains and regret functions to find an appropriate compromise in the context of multicriteria decision analysis (MCDA). This method was an innovation in the relationship between uncertainty and decision parameters, and it allows for a much more robust sensitivity analysis. The proposed approach avoids the drawbacks of arbitrary user-defined and method-specific parameters by defining transition rates that depend only upon the performances of the alternatives. This results in a flexible and easy-to-use tool that is completely transparent, reproducible, and easy to interpret. Furthermore, because it is based on Markov chains, the model allows for a seamless and innovative treatment of uncertainty. We apply the approach to an oil and gas decommissioning problem, which seeks a responsible manner in which to dismantle and deactivate production facilities. The experiments, which make use of published data on the decommissioning of the field of Brent, account for 12 criteria and illustrate the application of the proposed approach.

Suggested Citation

  • Fernanda F. Moraes & Virgílio José M. Ferreira Filho & Carlos Eduardo Durange de C. Infante & Luan Santos & Edilson F. Arruda, 2022. "A Markov Chain Approach to Multicriteria Decision Analysis with an Application to Offshore Decommissioning," Sustainability, MDPI, vol. 14(19), pages 1-15, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12019-:d:922706
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    References listed on IDEAS

    as
    1. Kumar, Abhishek & Sah, Bikash & Singh, Arvind R. & Deng, Yan & He, Xiangning & Kumar, Praveen & Bansal, R.C., 2017. "A review of multi criteria decision making (MCDM) towards sustainable renewable energy development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 596-609.
    2. Saaty, Thomas L., 1990. "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 48(1), pages 9-26, September.
    3. Peter C. Fishburn, 1967. "Letter to the Editor—Additive Utilities with Incomplete Product Sets: Application to Priorities and Assignments," Operations Research, INFORMS, vol. 15(3), pages 537-542, June.
    4. L C Dias & J N Clímaco, 2000. "Additive aggregation with variable interdependent parameters: the VIP analysis software," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(9), pages 1070-1082, September.
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