TY - JOUR
T1 - Scheduling stochastic jobs with increasing hazard rate on identical parallel machines
AU - Xu, Susan H.
AU - Kumar, Srikanta P.R.
AU - Mirchandani, Pitu B.
N1 - Funding Information:
Acknowledgements-The authorst hank the two reviewersw hosec ommentsa nd suggestionism provedt he presentationo f the resultsT. his work was partiallys upportedb y NSF Grant ECS-8307232.
PY - 1992/8
Y1 - 1992/8
N2 - We consider a discrete time model of m identical machines operating in parallel to complete a collection of jobs. The processing times of the jobs are independent, identically distributed discrete random variables having increasing hazard rate. The jobs may have received different amounts of prior processing. A reward βt, 0 < β < 1, is acquired when a job is finished at time t. We show that a non-preemptive SEPT (Shortest Expected Processing Time) strategy maximizes the expected total reward among all possible policies. We show that SEPT strategy is still optimal for several generalizations of this problem scenario.
AB - We consider a discrete time model of m identical machines operating in parallel to complete a collection of jobs. The processing times of the jobs are independent, identically distributed discrete random variables having increasing hazard rate. The jobs may have received different amounts of prior processing. A reward βt, 0 < β < 1, is acquired when a job is finished at time t. We show that a non-preemptive SEPT (Shortest Expected Processing Time) strategy maximizes the expected total reward among all possible policies. We show that SEPT strategy is still optimal for several generalizations of this problem scenario.
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U2 - 10.1016/0305-0548(92)90008-S
DO - 10.1016/0305-0548(92)90008-S
M3 - Article
AN - SCOPUS:0026909487
SN - 0305-0548
VL - 19
SP - 535
EP - 543
JO - Computers and Operations Research
JF - Computers and Operations Research
IS - 6
ER -