Multi-Modal Parameter Identification by Automata Approach
Journal
Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A/Chung-kuo Kung Ch'eng Hsuch K'an
Journal Volume
16
Journal Issue
5
Pages
603-613
Date Issued
1993
Date
1993
Author(s)
Kuo, Te-Son
Abstract
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 theautomaton converges to the global optimum with a probability arbitrarily closeto 1. The numerical simulation results show that the automata approach isbetter 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. © 1993 Taylor & Francis Group, LLC.
Subjects
Learning automata; Multi-modal optimization; Weak law of large number
Other Subjects
Applications; Mathematical models; Numerical methods; Optimization; Simulation; Automata model; Global optimization; Multi modal function optimization; Automata theory
Type
journal article