A New Hybrid Algorithm for Optimization Using PSO and GDA

In this paper a new combined approach is presented known as PSO-Great Deluge; the main idea of this approach is to combine particle swarm optimization (PSO) with great deluge algorithm. In this approach, global search character of PSO and local search factor of great deluge algorithm are used based on series. At the first step, PSO algorithm is used to search around environment and its results are given to great deluge algorithm to search about taken results accurately. This approach is tested and its efficiency is compared with methods like Genetic Algorithm and standard PSO results. In this paper is shown that this approach has considerable results

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