Paper Info
Title
The networked evolutionary algorithm: A network science perspective.
Abstract
The evolutionary algorithm is one of the most popular and effective methods to solve complex non-convex optimization problems in different areas of research. In this paper, we systematically explore the evolutionary algorithm as a networked interaction system, where nodes represent information process units and connections denote information transmission links. Within this networked evolutionary algorithm framework, we analyze the effects of structure and information fusion strategies, and further implement it in three typical evolutionary algorithms, namely in the genetic algorithm, the particle swarm optimization algorithm, and in the differential evolution algorithm. Our results demonstrate that the networked evolutionary algorithm framework can significantly improve the performance of these evolutionary algorithms. Our work bridges two traditionally separate areas, evolutionary algorithms and network science, in the hope that it promotes the development of both.
Year
DOI
Venue
2018
10.1016/j.amc.2018.06.002
Applied Mathematics and Computation
Keywords
Field
DocType
Evolutionary algorithm,Network system,Structure,Behavior
Network science,Particle swarm optimization,Mathematical optimization,Information processing,Evolutionary algorithm,Information transmission,Artificial intelligence,Optimization problem,Genetic algorithm,Differential evolution algorithm,Mathematics
Journal
Volume
ISSN
Citations 
338
0096-3003
3
PageRank 
References 
Authors
0.38
12
7
Name
Order
Citations
PageRank
Wen-Bo Du1346.64
Mingyuan Zhang2222.84
Wen Ying361.09
Perc Matjaž457058.27
Tang Ke52798139.09
Xianbin Cao660960.26
Dapeng Wu74463325.77