Discussion on convergence of a fuzzy adaptive simulated annealing genetic algorithm

ABSTRACT

Due to shortcomings of genetic algorithm that its convergence speed is slow and it is often premature convergence, a new improved genetic algorithm--fuzzy adaptive simulated annealing genetic algorithm (FASAGA) is presented by integrating fuzzy inference, simulated annealing algorithm and adaptive mechanism. The strong Markovian property attributed to the population sequence was deduced by mathematical modeling. Then the convergence in probability of the fuzzy adaptive simulated annealing genetic algorithm was proved on the condition that the time tended to infinity. The results show that the methods are helpful for directing choice of better FASAGA parameters and improving the performance of the algorithm.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.3 Deduction and Theorem Proving

General Terms:
Algorithms, Theory

Keywords:
adaptive, convergence, fuzzy inference, genetic algorithm, simulated annealing