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

Author

Listed:
  • 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
    School of Mathematics and Information Science, 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)

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.

Suggested Citation

  • Huimin Wang & Yuelin Gao & Yahua He, 2024. "Hybrid Sine Cosine and Particle Swarm Optimization Algorithm for High-Dimensional Global Optimization Problem and Its Application," Mathematics, MDPI, vol. 12(7), pages 1-46, March.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:7:p:965-:d:1362986
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