PARALLEL GENETIC ALGORITHMS

被引：0
|
作者：
Linder, Marek
Sekaj, Ivan
机构：
来源：
MENDEL 2011 - 17TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING | 2011年
关键词：
Parallel genetic algorithms; coarse-grained; fine-grained; migration; overlapping populations;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Parallel genetic algorithms (PGA) can significantly improve the performance of genetic algorithms (GA). Therefore we have analyzed the influence of various parallel genetic algorithm architectures on the algorithm convergence rate. Several Coarse-grained PGA and Fine-grained PGA architectures are compared. From the important factors we selected the following: structure of the migration interconnections, number of migration interconnections and migration size. The performance of selected PGAs is demonstrated on test function minimisation experiments.
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页码：9 / 15
页数：7
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