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作者 Maripi, Jagadish Kumar
書名 An effective parallel particle swarm optimization algorithm and its performance evaluation
國際標準書號 9781124287249
book jacket
說明 52 p
附註 Source: Masters Abstracts International, Volume: 49-02, page: 1214
Adviser: Shahram Rahimi
Thesis (M.S.)--Southern Illinois University at Carbondale, 2010
Population-based global optimization algorithms including Particle Swarm Optimization (PSO) have become popular for solving multi-optima problems much more efficiently than the traditional mathematical techniques. In this research, we present and evaluate a new parallel PSO algorithm that provides a significant performance improvement as compared to the serial PSO algorithm. Instead of merely assigning parts of the task of serial version to several processors, the new algorithm places multiple swarms on the available nodes in which operate independently, while collaborating on the same task. With the reduction of the communication bottleneck as well the ability to manipulate the individual swarms independently, the proposed approach outperforms the original PSO algorithm and still maintains the simplicity and ease of implementation
School code: 0209
Host Item Masters Abstracts International 49-02
主題 Engineering, Computer
Artificial Intelligence
Computer Science
Alt Author Southern Illinois University at Carbondale. Computer Science
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