A hybrid ICA/PSO algorithm by adding independent countries for large scale global optimization

Authors:
Amirhossein Ghodrati;Mohammad V. Malakooti;Mansooreh Soleimani
Affiliations:
Computer Engineering Department, College of Nabi Akram, Tabriz, Iran;UAE Branch, Department of Computer Engineering, Islamic Azad University, Iran;UAE Branch, Department of Computer Engineering, Islamic Azad University, Iran
Venue:
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part III
Year:
2012

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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.