Multi‐modal parameter identification by automata approach
Zen‐Kwei Huang, Sheng‐De Wang, Te‐Son Kuo · Journal of the Chinese Institute of Engineers · 1993
In this paper, we consider the multi‐modal function optimization problem. An automata model with improved learning schemes is proposed to solve the global optimization problem. Theoretically, we prove that the automaton converges to the global optimum with a probability arbitrarily close to 1. The numerical simulation results show that the automata approach is better than both the well‐known gradient approach and the simulated annealing method. The simulation results also show that our automata model converges faster than the other existing models in the literature.