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A stochastic tabu search algorithm to align physician schedule with patient flow

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Abstract

In this study, we consider the pretreatment phase for cancer patients. This is defined as the period between the referral to a cancer center and the confirmation of the treatment plan. Physicians have been identified as bottlenecks in this process, and the goal is to determine a weekly cyclic schedule that improves the patient flow and shortens the pretreatment duration. High uncertainty is associated with the arrival day, profile and type of cancer of each patient. We also include physician satisfaction in the objective function. We present a MIP model for the problem and develop a tabu search algorithm, considering both deterministic and stochastic cases. Experiments show that our method compares very well to CPLEX under deterministic conditions. We describe the stochastic approach in detail and present a real application.

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Authors and Affiliations

  1. CIRRELT and Polytechnique Montreal, CP6079 Succ Centre-ville, H3C 3A7, Montreal, QC, Canada

    Nazgol Niroumandrad & Nadia Lahrichi

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  1. Nazgol Niroumandrad
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  2. Nadia Lahrichi
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Correspondence to Nadia Lahrichi.

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Niroumandrad, N., Lahrichi, N. A stochastic tabu search algorithm to align physician schedule with patient flow. Health Care Manag Sci 21, 244–258 (2018). https://doi.org/10.1007/s10729-017-9427-1

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  • DOI: https://doi.org/10.1007/s10729-017-9427-1

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