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An approximate dynamic programing approach to the development of heuristics for the scheduling of impatient jobs in a clearing system
Author(s) -
Li Dong,
Glazebrook Kevin D.
Publication year - 2010
Publication title -
naval research logistics (nrl)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.665
H-Index - 68
eISSN - 1520-6750
pISSN - 0894-069X
DOI - 10.1002/nav.20395
Subject(s) - heuristics , computer science , mathematical optimization , heuristic , scheduling (production processes) , schedule , operations research , clearing , limit (mathematics) , job shop scheduling , mathematics , economics , mathematical analysis , finance , operating system
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 π S ) operates a static priority among the job classes and works well in a “no premature job loss” limit, whereas the second (π 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 π S , in which we use a fluid model to obtain an approximation for the value function of π S . The performance of the proposed heuristic is investigated in an extensive numerical study. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 2010