Abstract
A single server is faced with a collection of jobs of varying duration and urgency. Each job has a random lifetime during which it is available for nonpreemptive service. Should a job's lifetime expire before its service begins then it is lost from the system unserved. The goal is to schedule the jobs for service to maximize the expected number served to completion. Two heuristics have been proposed in the literature. One (labeled pi(S)) operates a static priority among the job classes and works well in a "no premature job loss" limit, whereas the second (pi(M)) is a myopic heuristic which works well when lifetimes are short. Both can exhibit poor performance for problems at some distance from the regimes for which they were designed. We develop a robustly good heuristic by an approximative approach to the application of a policy improvement step to the asymptotically optimal heuristic pi(S), in which we use a fluid model to obtain an approximation for the value function of pi(S). The performance of the proposed heuristic is investigated in an extensive numerical study. (C) 2010 Wiley Periodicals, Inc. Naval Research Logistics 57: 225-236, 2010
| Original language | English |
|---|---|
| Pages (from-to) | 225-236 |
| Number of pages | 12 |
| Journal | Naval Research Logistics |
| Volume | 57 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Apr 2010 |