Hybrid Sine Cosine and Particle Swarm Optimization Algorithm for High-Dimensional Global Optimization Problem and Its Application

Huimin Wang, Yuelin Gao () and Yahua He
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Huimin Wang: School of Computer Science and Engineering, North Minzu University, Yinchuan 750021, China
Yuelin Gao: School of Computer Science and Engineering, North Minzu University, Yinchuan 750021, China
Yahua He: Ningxia Collaborative Innovation Center for Scientific Computing and Intelligent Information Processing, North Minzu University, Yinchuan 750021, China

Mathematics, 2024, vol. 12, issue 7, 1-45

Abstract: Particle Swarm Optimization (PSO) is facing more challenges in solving high-dimensional global optimization problems. In order to overcome this difficulty, this paper proposes a novel PSO variant of the hybrid Sine Cosine Algorithm (SCA) strategy, named Velocity Four Sine Cosine Particle Swarm Optimization (VFSCPSO). The introduction of the SCA strategy in the velocity formulation ensures that the global optimal solution is found accurately. It increases the flexibility of PSO. A series of experiments are conducted on the CEC2005 test suite with compositional algorithms, algorithmic variants, and good intelligent algorithms. The experimental results show that the algorithm effectively improves the overall performance of compositional algorithms; the Friedman test proves that the algorithm has good competitiveness. The algorithm also performs better in PID parameter tuning. Therefore, the VFSCPSO is able to solve the high-dimensional global optimization problems in a better way.

Keywords: Particle Swarm Optimization; Sine Cosine Algorithm; hybrid algorithm; high-dimensional global optimization problem (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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