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

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