An Improved Genetic Algorithm for Power Grid

被引：1
|
作者：
Zhu, Youchan [1 ]
Guo, Xueying [1 ]
Li, Jing [1 ]
机构：
[1] N China Elect Power Univ, Network Management Ctr, Baoding 071003, Hebei Province, Peoples R China
来源：
FIFTH INTERNATIONAL CONFERENCE ON INFORMATION ASSURANCE AND SECURITY, VOL 1, PROCEEDINGS | 2009年
关键词：
Power Grid; Genetic algorithm; Min-min; Evolutionary process; DAG;
D O I：
10.1109/IAS.2009.86
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In Power Grid, we focus oil one kind of high performance computing applications, that is, Power system Computing and Simulation(PCS) applications. PCS applications are always broken down into several sub-tasks depending oil each other, which can be represented as a DAG. Genetic Algorithm(GA) has been widely used to solve the dependent tasks scheduling. However the conventional GA is too slow to be used in Power Grid due to its time-consuming iteration. This paper applies an Improved Genetic Algorithm(IGA) to dependent tasks scheduling in Power Grid. Based oil the characteristic of Power Grid scheduling, we design detailedly the Chromosome Presentation, Fitness Function, and Evolutionary Process. And. this algorithm increases search efficiency with limited number of iteration by improving the evolutionary process while meeting a feasible result. An simulation study was conducted to evaluate the performance of the algorithm. It showed the general suitability of the presented algorithm within Power Grid.
引用
收藏
页码：455 / 458
页数：4
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