From Determinism and Probability to Chaos: Chaotic Evolution towards Philosophy and Methodology of Chaotic Optimization

Figure 3

Interactive chaotic evolution convergent curves of 5D, 10D, 15D, and 20D Gaussian mixture model. All the ICE algorithms present fast convergent speed, especially in 10D and 20D tasks. IDE/best can obtain better final results than ICE, but it needs more fitness evaluation (i.e., more human subjective evaluation in IEC application) to find the best base vector. From the metric of fitness evaluation time, ICE is significantly better than IDE/best when these two algorithms call the same fitness function time.

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