The Spiral Optimization Algorithm: Convergence Conditions and Settings
研究了螺旋优化算法的收敛条件，提出确保算法收敛到稳定点的数学条件，并通过测试函数验证。
The spiral optimization (SPO) algorithm proposed by Tamura and Yasuda is a relatively novel and simple search concept inspired by natural spiral phenomena. This algorithm searches continuous space using no gradient and only spiral trajectories composed of spiral vectors generated by deterministic spiral models. The primary purpose of this paper is to propose conditions and settings that mathematically ensure the convergence of the SPO algorithm to a stationary point. The conditions relating to the sizes and directions of the spiral vectors and the initial search points are based on direct search theory and recent SPO algorithm theories. The presented convergence was numerically verified using test functions with different properties.