A Diffusion Approximation for a Markovian Queue with Reneging
Queueing Systems: Theory and Applications
Integrating Replenishment Decisions with Advance Demand Information
Management Science
Approximate Solutions of a Dynamic Forecast-Inventory Model
Manufacturing & Service Operations Management
Managing Patient Service in a Diagnostic Medical Facility
Operations Research
Dynamic Multipriority Patient Scheduling for a Diagnostic Resource
Operations Research
Dynamic Scheduling of Outpatient Appointments Under Patient No-Shows and Cancellations
Manufacturing & Service Operations Management
Approximation algorithms for stochastic inventory control models
IPCO'05 Proceedings of the 11th international conference on Integer Programming and Combinatorial Optimization
Hi-index | 0.00 |
Motivated by service capacity-management problems in healthcare contexts, we consider a multiresource allocation problem with two classes of jobs elective and emergency in a dynamic and nonstationary environment. Emergency jobs need to be served immediately, whereas elective jobs can wait. Distributional information about demand and resource availability is continually updated, and we allow jobs to renege. We prove that our formulation is convex, and the optimal amount of capacity reserved for emergency jobs in each period decreases with the number of elective jobs waiting for service. However, the optimal policy is difficult to compute exactly. We develop the idea of a limit policy starting at a particular time, and use this policy to obtain upper and lower bounds on the decisions of an optimal policy in each period, and also to develop several computationally efficient policies. We show in computational experiments that our best policy performs within 1.8% of an optimal policy on average.