An elective surgery scheduling problem considering patient priority
Computers and Operations Research
MRI reservation for neurovascular patients
CASE'09 Proceedings of the fifth annual IEEE international conference on Automation science and engineering
Dynamic Scheduling of Outpatient Appointments Under Patient No-Shows and Cancellations
Manufacturing & Service Operations Management
Appointment Scheduling with Discrete Random Durations
Mathematics of Operations Research
A Markov decision process approach to multi-category patient scheduling in a diagnostic facility
Artificial Intelligence in Medicine
Lagrangian relaxation and constraint generation for allocation and advanced scheduling
Computers and Operations Research
A decision support system for patient scheduling in travel vaccine administration
Decision Support Systems
Manufacturing & Service Operations Management
Performance-Based Contracts for Outpatient Medical Services
Manufacturing & Service Operations Management
Comparing two operating-room-allocation policies for elective and emergency surgeries
Proceedings of the Winter Simulation Conference
Multiresource Allocation Scheduling in Dynamic Environments
Manufacturing & Service Operations Management
A sequential GRASP for the therapist routing and scheduling problem
Journal of Scheduling
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We present a method to dynamically schedule patients with different priorities to a diagnostic facility in a public health-care setting. Rather than maximizing revenue, the challenge facing the resource manager is to dynamically allocate available capacity to incoming demand to achieve wait-time targets in a cost-effective manner. We model the scheduling process as a Markov decision process. Because the state space is too large for a direct solution, we solve the equivalent linear program through approximate dynamic programming. For a broad range of cost parameter values, we present analytical results that give the form of the optimal linear value function approximation and the resulting policy. We investigate the practical implications and the quality of the policy through simulation.