A Parameter Setting Method for Spiral Optimization from Stability Analysis of Dynamic Equilibrium Point
Kenichi Tamura, Keiichiro Yasuda · SICE Journal of Control Measurement and System Integration · 2014
In recent years, the authors have proposed an effective metaheuristic method for continuous optimization problems based on an analogy of spiral phenomena in nature. This method is called Spiral Optimization (SPO). SPO has two setting parameters: the convergence rate and the rotation rate. Depending on computational and/or problem conditions, the values of these parameters affect search performance. However, effective setting methods for these parameters without trial and error, including analyses of search dynamics needed for such methods, have not yet been studied. This paper analyzes the stability of the dynamic equilibrium point of the SPO model and proposes a parameter-setting method for the convergence rate r based on results from stability analysis. The effectiveness of the proposed method is confirmed through simulation for some benchmark functions and comparison with other representative metaheuristic methods.