A Novel Hybrid Particle Swarm Optimization and Sine Cosine Algorithm for Seismic Optimization of Retaining Structures

This study introduces an effective hybrid optimization algorithm, namely Particle Swarm Sine Cosine Algorithm (PSSCA) for numerical function and automating optimum design of retaining structures under seismic loads. The new algorithm employs the dynamic behavior sine cosine functions in velocity updating operation particle swarm (PSO) to achieve faster convergence better accuracy final solution without getting trapped local minima. proposed is tested over a set 16 benchmark results are compared with other well-known algorithms field optimization. For structure, Mononobe-Okabe method employed loading condition total construction cost structure considered as objective function. Finally, two static from literature. As demonstrate, PSSCA superior it could generate optimal solutions competitive algorithms.