Scheduling of Multi-Class Single-Server Queues Under Nontraditional Performance Measures

Hayriye Ayhan () and Tava Lennon Olsen ()
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Hayriye Ayhan: School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0205
Tava Lennon Olsen: Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan, 48109-2117

Operations Research, 2000, vol. 48, issue 3, 482-489

Abstract: We consider a multi-class production system without setups where many job classes share a single server. The traditional performance measure used for scheduling these systems is that of mean throughput time (i.e., the time spent in the system). However, mean throughput time may not be the only measure of importance in real systems. In particular, throughput time variance and the outer percentiles of throughput time may be equally important. We present two heuristics for scheduling multi-class single-server queues that are based on heavy-traffic analysis and perform well with respect to these nontraditional measures in a wide variety of cases. An approximation is given for the throughput time distribution under both scheduling methods.

Keywords: Production scheduling; sequencing; stochastic: multi-item single-machine; Production scheduling; approximation/heuristic: heavy-traffic; multi-item single-machine (search for similar items in EconPapers)
Date: 2000
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Citations: View citations in EconPapers (5)

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