抄録
An optimization method based on piecewise-rotational chaotic system (OPRC) is proposed. OPRC is a kind of multi-point searching methods in order to find an optimal solution, and these searching points are updated by piecewise-rotational chaotic dynamics. OPRC is a simple optimizer because these searching points are governed by simple dynamics which contains no stochastic terms. OPRC has significantly better performance than particle swarm optimization and our previous method based on another chaotic system. The relationship between the performance of OPRC and the time-series of the proposed chaotic system is analyzed. Then we clarify that OPRC obtains better solutions when the autocorrelation of the time-series takes negative values with damped oscillation.
