COMPARISON OF SOME PARALLEL GENETIC ALGORITHMS WITH POPULATION REINITIALIZATION

被引：0
|
作者：
Sekaj, I. [1 ]
Oravec, M. [1 ]
机构：
[1] Slovak Tech Univ Bratislava, Fac Elect Engn & Informat Technol, Inst Control & Ind Informat, Bratislava 81219, Slovakia
来源：
MENDELL 2009 | 2009年
关键词：
parallel evolutionary algortihm; parallel genetic algorithm; population; fine-grained; coarse-grained; reinitialization;
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：
In solving many practical search/optimization problems using evolutionary algorithms it is often difficult to avoid the premature convergence in search for the global optimum. From that reason parallel evolutionary algorithms (PEA) and Parallel Genetic Algorithms (PGA) can be used more effectively. In this paper some selected fine- and coarse-grained PGA architectures are analyzed and experimentally compared. Also the influence of population reinitialization on the parallel genetic algorithm performance is analyzed The results are demonstrated on the minimization of selected test functions.
引用
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页码：23 / 28
页数：6
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