Central intake optimization and decentralized decomposition for appointment scheduling and sequencing

Pardis Seyedi (), Michael W. Carter and Kourosh Eshghi
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Pardis Seyedi: Sharif University of Technology
Michael W. Carter: University of Toronto
Kourosh Eshghi: Sharif University of Technology

Flexible Services and Manufacturing Journal, 2025, vol. 37, issue 1, No 8, 208-253

Abstract: Abstract An efficient appointment scheduling system has a defining role in controlling wait times and improving the productivity of a large variety of service systems. This study addresses the variability and length of wait times. We reduce them by a form of restricted central intake. We believe it is the first study that expands the appointment scheduling-sequencing model to include multiple sites and incorporate clients’ flexibility and priorities, and solves the large-size scheduling-sequencing problem in a decentralized manner. To make the study more practical, it should be compatible with the multi-stakeholder environment and consider their independency. Furthermore, the problem is large-size as it combines all requests from a geographical region into one stream. Therefore, a decentralized distributed algorithm is applied to solve the amended model. The solution approach is an ADMM-based combination of dual decomposition and augmented Lagrangian relaxation. For the application of this approach, this paper focuses on the outpatient appointment system due to its importance. Early diagnosis and prevention play a crucial role in community health and health system quality. However, patients often experience significant wait times for various diagnostic technologies worldwide. The approach is examined by a real situation of MRI in Ontario, Canada. It has been shown that this study provides better workload balance across hospitals, better responding to demand fluctuations, and alleviates excessive wait times. The computational results also show that the proposed solution method can be satisfactory in terms of accuracy, running time, and applicability. The approach developed in this study can be applicable to many practical applications of timing and sequencing, such as outpatient surgery, other diagnostic testing, home healthcare, and physical and mental therapies, as well as in other service industries beyond healthcare, like public consultations, government services.

Keywords: Operations research; Appointment scheduling/sequencing; Healthcare management; Decentralized solution; Distributed algorithm; Service operations management; Central intake (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10696-024-09538-w

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