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Background: Start-up, shutdown, and turnaround operations arising from frequent and pandemic-induced activities lead to an exposure of crude distillation units in refineries to various risks associated with health, technology, economics, organisation, and society, and it is a difficult task to decide on whether the CDU should continue to operate, be shut down, or shut down and maintained using classical crisp approaches to decision-making. Objective: The current paper proposes an integrated benefit-cost analysis of interval-valued intuitionistic fuzzy analytic hierarchy process to rank four possible alternatives of refinery operation during pandemic times, namely, continuing the operation of the unit, shutdown without maintenance, shutdown with CBM, and shutdown with OM. Methods: An expert panel of seven members (average experience 16.4 years), selected based on specified selection criteria, generated 5 main criteria, 25 sub-criteria and 4 alternative courses of action. Interval-valued intuitionistic fuzzy preferences for pair-wise comparisons were gathered, aggregated based on score and accuracy functions and further translated into priority weights using interval multiplicative preference matrix and possibility degree methodology. Expert judgement consistency was ensured by applying a consistency ratio (CR) measure along with a Delphi type consensus methodology. Robustness of prioritization was analyzed by performing sensitivity analysis on the relative weighting parameter for benefits-costs (wᴬ=0.30 to 0.70). Results: The highest B/C was achieved for shutdown without maintenance (B/C = 1.131) followed by shutdown with CBM (B/C = 0.987), shutdown with OM (B/C = 0.964), and shutdown without maintenance (B/C = 0.945; the lowest). The order of the best alternative was constant among all nine sensitivity cases (Kendall τ ≥ 0.67 in each of them), and consistency ratio at criteria level for goal level matrices (CR = 0.09–0.17) indicated sufficient expert consensus. Conclusion: The proposed approach of IVIFAHP-BCA can be applied as a robust decision-making method under uncertainty in refinery shutdowns during pandemics.
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Suresh et al. (2026) studied this question.
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