EXPERIMENTAL COMPARISON OF SELECTED TYPES OF PARALLEL EVOLUTIONARY ALGORITHMS

被引：0
|
作者：
Sekaj, Ivan [1 ]
Linder, Marek [1 ]
Pernecky, Daniel [1 ]
机构：
[1] Slovak Univ Technol Bratislava, Fac Elect Engn & Informat Technol, Inst Control & Ind Informat, Ilkovicova 3, Bratislava 81219, Slovakia
来源：
ECTA 2011/FCTA 2011: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON EVOLUTIONARY COMPUTATION THEORY AND APPLICATIONS AND INTERNATIONAL CONFERENCE ON FUZZY COMPUTATION THEORY AND APPLICATIONS | 2011年
关键词：
Evolutionary Algorithm; Genetic Algorithm; Parallelisation; Architecture; Migration; Overlapping; Experimental Comparison;
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 evolutionary algorithms are able to improve the performance of simple evolutionary algorithms which use a single population. Their characteristics and performance depend on their architectures and other factors and parameters. In our contribution we present some viewpoints of classification and we demonstrate experimentally the influence of selected factors such as architecture type, migration topology, migration period, number of migrants, numbers of subpopulations, subpopulation size and others on the performance of these algorithms. This experimental study should help to generalise the properties and behaviour of various types of parallel evolutionary algorithms and help to design algorithms for solving hard search/optimisation problems like modelling of bio-medicine processes, optimisation of pharmaceutical dosing, optimisation of large technological and construction tasks etc.
引用
收藏
页码：296 / 302
页数：7
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