Mathematical Programming: Series A and B
On Steepest Descent Algorithms for Discrete Convex Functions
SIAM Journal on Optimization
Managing Patient Service in a Diagnostic Medical Facility
Operations Research
Submodular function minimization
Mathematical Programming: Series A and B
Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems
A faster strongly polynomial time algorithm for submodular function minimization
Mathematical Programming: Series A and B
Appointment scheduling with discrete random durations
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Scheduling Arrivals to Queues: A Single-Server Model with No-Shows
Management Science
Dynamic Multipriority Patient Scheduling for a Diagnostic Resource
Operations Research
Revenue Management for a Primary-Care Clinic in the Presence of Patient Choice
Operations Research
On the Structure of Lost-Sales Inventory Models
Operations Research
Technical Note---A Sampling-Based Approach to Appointment Scheduling
Operations Research
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We consider the problem of determining an optimal appointment schedule for a given sequence of jobs (e.g., medical procedures) on a single processor (e.g., operating room, examination facility, physician), to minimize the expected total underage and overage costs when each job has a random processing duration given by a joint discrete probability distribution. Simple conditions on the cost rates imply that the objective function is submodular and L-convex. Then there exists an optimal appointment schedule that is integer and can be found in polynomial time. Our model can handle a given due date for the total processing (e.g., end of day for an operating room) after which overtime is incurred, as well as no-shows and some emergencies.