Due-date setting and priority sequencing in a multiclass M/G/1 queue

Includes bibliographical references (leaves 26-28).by Lawrence M. Wein

Queueing theory and operations management.

Management; Theory;

Modeling a healthcare system as a queueing network:The case of a Belgian hospital.

The performance of health care systems in terms of patient flow times and utilization of critical resources can be assessed through queueing and simulation models. We model the orthopaedic department of the Middelheim hospital (Antwerpen, Belgium) focusing on the impact of outages (preemptive and nonpreemptive outages) on the effective utilization of resources and on the flowtime of patients. Several queueing network solution procedures are developed such as the decomposition and Brownian motion approaches. Simulation is used as a validation tool. We present new approaches to model outages. The model offers a valuable tool to study the trade-off between the capacity structure, sources of variability and patient flow times.Belgium; Brownian motion; Capacity management; Decomposition; Health care; Healthcare; Impact; Model; Models; Performance; Performance measurement; Queueing; Queueing theory; Simulation; Stochastic processes; Structure; Studies; Systems; Time; Tool; Validation; Variability;

Resource Allocation Strategies for Multiple Job Classes

Resource management for a data center with multiple job classes is investigated in this thesis. We focus on strategies for allocating resources to an application mix such that the service level agreements (SLAs) of individual applications are met. A performance model with two interactive job classes is used to determine the smallest number of processor nodes required to meet the SLAs of both classes. For each class, the SLA is specified by the relationship: Prob(response time≤x)≥y. Two allocation strategies are considered: shared allocation (SA) and dedicated allocation (DA). For the case of FCFS scheduling, analytic results for response time distribution are used to develop a heuristic algorithm that determines the allocation strategy (SA or DA) that requires fewer processor nodes. The effectiveness of this algorithm is evaluated over a range of operating conditions. The performance of SA with non-FCFS scheduling is also investigated. Among the scheduling disciplines considered, a new discipline called probability dependent priority (PDP) is found to have the best performance in terms of requiring the smallest number of nodes. Furthermore, we extend our heuristic algorithm for FCFS to three job classes. The effectiveness of this extended algorithm is evaluated. As to priority scheduling, the performance advantage of PDP is also confirmed for the case of three job classes