Open AccessA Novel Hybrid Particle Swarm Optimization and Sine Cosine Algorithm for Seismic Optimization of Retaining Structures
Author(s) -
Mohammad Khajehzadeh,
Seyed Alireza Sobhani,
Seyed Mehdi Seyed Alizadeh,
Mahdiyeh Eslami
Publication year - 2021
Publication title -
periodica polytechnica. civil engineering/periodica polytechnica. civil engineering (online)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.406
H-Index - 19
eISSN - 1587-3773
pISSN - 0553-6626
DOI - 10.3311/ppci.19027
Subject(s) - particle swarm optimization , trigonometric functions , maxima and minima , sine , benchmark (surveying) , algorithm , multi swarm optimization , mathematical optimization , convergence (economics) , computer science , derivative free optimization , meta optimization , function (biology) , optimization problem , mathematics , mathematical analysis , geometry , geodesy , evolutionary biology , economic growth , economics , biology , geography
This study introduces an effective hybrid optimization algorithm, namely Particle Swarm Sine Cosine Algorithm (PSSCA) for numerical function optimization and automating optimum design of retaining structures under seismic loads. The new algorithm employs the dynamic behavior of sine and cosine functions in the velocity updating operation of particle swarm optimization (PSO) to achieve faster convergence and better accuracy of final solution without getting trapped in local minima. The proposed algorithm is tested over a set of 16 benchmark functions and the results are compared with other well-known algorithms in the field of optimization. For seismic optimization of retaining structure, Mononobe-Okabe method is employed for dynamic loading condition and total construction cost of the structure is considered as the objective function. Finally, optimization of two retaining structures under static and seismic loading are considered from the literature. As results demonstrate, the PSSCA is superior and it could generate better optimal solutions compared with other competitive algorithms.