Title
A hybrid ICA/PSO algorithm by adding independent countries for large scale global optimization
Abstract
This paper presents the hybrid approach of Imperialist Competitive Algorithm (ICA) and Particle Swarm Optimization (PSO) for global optimization. In standard ICA, there are only two types of countries: imperialists and colonies. In the proposed hybrid algorithm (ICA/PSO) we added another type of country, ‘Independent'. Independent countries do not fall into the category of empires, and are anti-imperialism. In addition, they are united and their shared goal is to get stronger in order to rescue colonies and help them join independent countries. These independent countries are aware of each other positions and make use of swarm intelligence in PSO for their own progress. Experimental results are examined with benchmark functions provided by CEC2010 Special Session on Large Scale Global Optimization (LSGO) and the results are compared with some previous LSGO algorithms, standard PSO and standard ICA.
Year
DOI
Venue
2012
10.1007/978-3-642-28493-9_12
ACIIDS (3)
Keywords
Field
DocType
particle swarm optimization,proposed hybrid algorithm,pso algorithm,previous lsgo algorithm,cec2010 special session,standard pso,large scale,large scale global optimization,standard ica,hybrid ica,hybrid approach,global optimization,independent country,imperialist competitive algorithm,swarm intelligence
Particle swarm optimization,Mathematical optimization,Hybrid algorithm,Global optimization,Computer science,Swarm intelligence,Artificial intelligence,Imperialist competitive algorithm,Machine learning
Conference
Volume
ISSN
Citations 
7198
0302-9743
1
PageRank 
References 
Authors
0.35
9
3
Name
Order
Citations
PageRank
Amirhossein Ghodrati1221.54
Mohammad V. Malakooti231.75
Mansooreh Soleimani310.35