Sand Cat Swarm Optimization Based on Stochastic Variation With Elite Collaboration

• Published in: IEEE access Vol. 10; pp. 89989 - 90003
• Main Authors: Li, Yiming, Wang, Gencheng
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Behavioral sciences; Collaboration; Convergence; elite collaboration; Heuristic algorithms; Machine learning; Metaheuristics; nonlinear periodic adjustment; Nonlinear systems; Optimization; Optimization algorithms; Particle swarm optimization; Performance enhancement; Sand; Sand cat swarm optimization; Search algorithms; Statistics; Stochastic processes; stochastic variation; Trigonometric functions

The sand cat swarm optimization (SCSO) is a new heuristic optimization algorithm that simulates the behavior of sand cat groups in the desert using hearing to hunt. To address the shortcomings of low accuracy of SCSO solution, slow convergence in late iterations and easy convergence stagnation, a sa...