SYNCHRONOUS AND ASYNCHRONOUS MIGRATION IN ADAPTIVE DIFFERENTIAL EVOLUTION ALGORITHMS

被引：8
|
作者：
Bujok, Petr [1 ]
机构：
[1] Univ Ostrava, Dept Informat & Comp, Ostrava, Czech Republic
来源：
NEURAL NETWORK WORLD | 2013年 / 23卷 / 01期
关键词：
Differential evolution; parallel migration model; synchronous migration; asynchronous migration; benchmark problems; experimental comparison; GLOBAL OPTIMIZATION; PARAMETERS;
D O I：
10.14311/NNW.2013.23.002
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The influence of synchronous and asynchronous migration on the performance of adaptive differential evolution algorithms is investigated. Six adaptive differential evolution variants are employed by the parallel migration model with a star topology. Synchronous and asynchronous migration models with various parameters settings were experimentally compared with non-parallel adaptive algorithms in six shifted benchmark problems of dimension D = 30. Three different ways of exchanging individuals are applied in a synchronous island model with a fixed number of islands. Three different numbers of sub-populations are set up in an asynchronous island model. The parallel synchronous and asynchronous migration models increase performance in most problems.
引用
收藏
页码：17 / 30
页数：14
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