Cooperative Group Search Optimization

Group Search Optimizer (GSO) is a population-based optimization approach inspired by animal searching behaviour and group living theory. Although competition among population members may improve their performance, greater improvements could be achieved through cooperation. In this paper, a new algor...

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Bibliographic Details
Main Authors: Pacifico, L. D. S., Ludermir, T. B.
Format: Conference Proceeding
Language:English
Subjects:
Animals
Cooperative learning
Evolutionary computing
Genetic algorithms
Group search optimization
Measurement
Optimization
Sociology
Statistics
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Summary:Group Search Optimizer (GSO) is a population-based optimization approach inspired by animal searching behaviour and group living theory. Although competition among population members may improve their performance, greater improvements could be achieved through cooperation. In this paper, a new algorithm is presented, called Cooperative Group Search Optimizer (CGSO), based on divide-and-conquer paradigm, employing cooperative behaviour among multiple GSO groups to improve the performance of standard GSO. Nine benchmark functions are used to evaluate the performance of the proposed technique. Experimental results show that the CGSO approach is able to achieve better results than standard GSO in most of the tested problems.
ISSN:1089-778X
1941-0026
DOI:10.1109/CEC.2013.6557974