A comment on “buffer space allocation in automated assembly lines”
Operations Research
On decomposition methods for tandem queueing networks with blocking
Operations Research
When should a roving server be patient?
Management Science
A Practical Scheduling Method for Multiclass Production Systems with Setups
Management Science
Analyzing queueing networks with simultaneous resource possession
Communications of the ACM
Exact Analysis of the State-Dependent Polling Model
Queueing Systems: Theory and Applications
Control of a Single-Server Tandem Queueing System with Setups
Operations Research
LIMIT THEOREMS FOR POLLING MODELS WITH INCREASING SETUPS
Probability in the Engineering and Informational Sciences
Throughput Maximization for Tandem Lines with Two Stations and Flexible Servers
Operations Research
Dynamic Multipriority Patient Scheduling for a Diagnostic Resource
Operations Research
Reducing Delays for Medical Appointments: A Queueing Approach
Operations Research
Optimal Capacity Overbooking for the Regular Treatment of Chronic Conditions
Operations Research
Dynamic Scheduling of Outpatient Appointments Under Patient No-Shows and Cancellations
Manufacturing & Service Operations Management
Optimal Allocation of Surgery Blocks to Operating Rooms Under Uncertainty
Operations Research
Operations Research
Nurse Staffing in Medical Units: A Queueing Perspective
Operations Research
On polling systems with large setups
Operations Research Letters
Polling systems with periodic server routing in heavy traffic: renewal arrivals
Operations Research Letters
Operations Research Letters
Dynamic Appointment Scheduling of a Stochastic Server with Uncertain Demand
INFORMS Journal on Computing
Hi-index | 0.00 |
We consider the work flow in a medical teaching facility, examining the process that involves an initial patient exam by a resident physician, a subsequent conference between the resident and the attending physician, and the attending physician's visit with the patient. We create an analytical model of a tandem queue with finite buffer space to analyze the impact of different work prioritization policies on the throughput and the flow time of patients in the facility---measures that influence both the facility's finances and patients' satisfaction. We derive throughput-optimal policies and show that these policies involve dynamic batching. This finding is interesting because our model does not include any setup times, and setup times normally imply batching; rather it is the uncertain service times and the requirement for simultaneous service in the conference step that make batching optimal. The optimal dynamic batching policy is complex, so we consider a simpler static batching policy. We show that, in systems with limited buffer space, large batches can sometimes degrade efficiency by simultaneously increasing flow time and decreasing throughput. However, in general, both flow time and throughput increase with batch size. Flow time increases at a faster rate than throughput, so hospital management may want to consider what batch size is optimal given the value it places on the two measures.