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A Stochastic Programming Model for Service Scheduling with Uncertain Demand: an Application in Open-Access Clinic Scheduling

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Abstract

This paper addressed a scheduling problem which handles urgent tasks along with existing schedules. The uncertainties in this problem come from random process of existing schedules and unknown upcoming urgent tasks. To deal with the uncertainties, this paper proposes a stochastic integer programming (SIP) based aggregated online scheduling method. The method is illustrated through a study case from the outpatient clinic block-wise scheduling system which is under a hybrid scheduling policy combining regular far-in-advance policy and the open-access policy. The COVID-19 pandemic brings more challenges for the healthcare system including the fluctuations of service time and increasing urgent requests which this paper is designed for. The schedule framework designed in the method is comprehensive to accommodate various uncertainties in the healthcare service system, such as: no-shows, cancellations and punctuality of patients as well as preference of patients over time slots and physicians.

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Data Availability

The initial data on patient arrival and patient service times was obtained from a local clinic under a confidentiality agreement that prevents us from disclosing the clinic information and the dataset. The data was aggregated to obtain the underlying distribution that was used and shown in Fig. 1 of the manuscript and Fig. 1 of the Appendix. The random data for the experiments were generated through Java code based on the parameters mentioned in Sects. 4.3 and 4.4. The algorithms in the paper were coded using Java and the different experimental scenarios were run using Java and CPLEX to produce the results that are discussed in the manuscript. Interested readers can contact the corresponding author to obtain a copy of the Java codes.

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  1. Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, USA

    Yu Fu & Amarnath Banerjee

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  1. Yu Fu
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Correspondence to Amarnath Banerjee.

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Fu, Y., Banerjee, A. A Stochastic Programming Model for Service Scheduling with Uncertain Demand: an Application in Open-Access Clinic Scheduling. SN Oper. Res. Forum 2, 43 (2021). https://doi.org/10.1007/s43069-021-00089-6

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