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Optimal Scheduling of Inspections: A Delayed Markov Model with False Positives and Negatives

Author

Listed:
  • Suleyman Özekici

    (Bogazici University, Bebek, Istanbul, Turkey)

  • Stanley R. Pliska

    (University of Illinois at Chicago, Chicago, Illinois)

Abstract

A system subject to catastrophic failure deteriorates according to a delayed Markov process and is subjected to a series of binary tests that may yield false negative and false positive outcomes. A corrective action is carried out when a true positive is observed, thereby reducing the chance of system failure. Costs of inspections, false positives, the corrective action, and failure are incurred, and dynamic programming is used to compute the optimal inspection schedule. Two tractable computational methods are developed. The model, which is suited for medical screening, is applied to the problems of post-operative periumbilical pruritis and breast cancer.

Suggested Citation

  • Suleyman Özekici & Stanley R. Pliska, 1991. "Optimal Scheduling of Inspections: A Delayed Markov Model with False Positives and Negatives," Operations Research, INFORMS, vol. 39(2), pages 261-273, April.
    • Handle: RePEc:inm:oropre:v:39:y:1991:i:2:p:261-273
    DOI: 10.1287/opre.39.2.261
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    Cited by:

    1. Yue Hu & Carri W. Chan & Jing Dong, 2022. "Optimal Scheduling of Proactive Service with Customer Deterioration and Improvement," Management Science, INFORMS, vol. 68(4), pages 2533-2578, April.
    2. Lisa M. Maillart & Julie Simmons Ivy & Scott Ransom & Kathleen Diehl, 2008. "Assessing Dynamic Breast Cancer Screening Policies," Operations Research, INFORMS, vol. 56(6), pages 1411-1427, December.
    3. Wenqi Hu & Carri W. Chan & José R. Zubizarreta & Gabriel J. Escobar, 2018. "An Examination of Early Transfers to the ICU Based on a Physiologic Risk Score," Manufacturing & Service Operations Management, INFORMS, vol. 20(3), pages 531-549, July.
    4. G. G. Hegde & Uday S. Karmarkar, 1993. "Engineering costs and customer costs in designing product support," Naval Research Logistics (NRL), John Wiley & Sons, vol. 40(3), pages 415-423, April.
    5. Aaron Ratcliffe & Ann Marucheck & Sean Xin Xu, 2019. "Regional Planning Model for Cancer Screening with Imperfect Patient Adherence," Service Science, INFORMS, vol. 11(2), pages 113-137, June.
    6. Wang, Fan & Zhang, Shengfan & Henderson, Louise M., 2018. "Adaptive decision-making of breast cancer mammography screening: A heuristic-based regression model," Omega, Elsevier, vol. 76(C), pages 70-84.
    7. Jonathan E. Helm & Mariel S. Lavieri & Mark P. Van Oyen & Joshua D. Stein & David C. Musch, 2015. "Dynamic Forecasting and Control Algorithms of Glaucoma Progression for Clinician Decision Support," Operations Research, INFORMS, vol. 63(5), pages 979-999, October.
    8. Turgay Ayer, 2015. "Inverse optimization for assessing emerging technologies in breast cancer screening," Annals of Operations Research, Springer, vol. 230(1), pages 57-85, July.
    9. Akcay, Alp, 2022. "An alert-assisted inspection policy for a production process with imperfect condition signals," European Journal of Operational Research, Elsevier, vol. 298(2), pages 510-525.
    10. Michael Jong Kim & Viliam Makis, 2013. "Joint Optimization of Sampling and Control of Partially Observable Failing Systems," Operations Research, INFORMS, vol. 61(3), pages 777-790, June.
    11. Hulisi Ogut & Huseyin Cavusoglu & Srinivasan Raghunathan, 2008. "Intrusion-Detection Policies for IT Security Breaches," INFORMS Journal on Computing, INFORMS, vol. 20(1), pages 112-123, February.
    12. Marion S. Rauner & Walter J. Gutjahr & Kurt Heidenberger & Joachim Wagner & Joseph Pasia, 2010. "Dynamic Policy Modeling for Chronic Diseases: Metaheuristic-Based Identification of Pareto-Optimal Screening Strategies," Operations Research, INFORMS, vol. 58(5), pages 1269-1286, October.
    13. Hao Zhang & Weihua Zhang, 2023. "Analytical Solution to a Partially Observable Machine Maintenance Problem with Obvious Failures," Management Science, INFORMS, vol. 69(7), pages 3993-4015, July.
    14. Turgay Ayer & Oguzhan Alagoz & Natasha K. Stout & Elizabeth S. Burnside, 2016. "Heterogeneity in Women’s Adherence and Its Role in Optimal Breast Cancer Screening Policies," Management Science, INFORMS, vol. 62(5), pages 1339-1362, May.

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