Abstract
In this article, search mechanisms of Swallow Swarm Optimization (SSO) are implemented in the framework of Particle Swarm Optimization (PSO) to form the Hybrid Particle Swallow Swarm Optimization (HPSSO) algorithm. The new algorithm is tested by solving eleven mathematical optimization problems and six truss weight minimization problems. HPSSO is compared to the standard PSO and some of its advanced variants. Optimization results demonstrate the efficiency of the proposed algorithm that outperforms the PSO variants taken as basis of comparison and is very competitive with other state-of-the-art metaheuristic optimization methods. Here, a good balance between global and local searches is achieved.
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