Automatic tuning of a fuzzy batch job scheduler using a genetic algorithm

被引：0
|
作者：
Shaout, A [1 ]
McAuliffe, P [1 ]
机构：
[1] Univ Michigan, Dept Elect & Comp Engn, Dearborn, MI 48128 USA
来源：
18TH INTERNATIONAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS | 1999年
关键词：
D O I：
10.1109/NAFIPS.1999.781671
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents the application ota genetic algorithm to automatically tune a fuzzy batch job schedule for maximum throughput. This genetic algorithm vades fuzzy membership functions, fuzzy rules and resource limits on processors to optimize for maximum job throughput and bad balancing: across processors of a distributed system. Unlike most research done in the realm of bad balancing and job scheduling this paper presents an algorithm that has been evaluated in a production processing environment rather than in simulation only.
引用
收藏
页码：144 / 148
页数：5
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