A Theoretical Comparison of Evolutionary Algorithms and Simulated Annealing
نویسنده
چکیده
This paper theoretically compares the performance of simulated annealing and evolutionary algorithms. Our main result is that under mild conditions a wide variety of evolutionary algorithms can be shown to have greater probability of success than simulated annealing after a suuciently large number of function evaluations. This class of EAs includes variants of evolution strategies and evolutionary programming, genetic programming , the canonical genetic algorithm, as well as a variety of genetic algorithms that have been applied to combinatorial optimization problems. The proof of this result is based on a performance analysis of a very general class of stochastic optimization algorithms, which has implications for the performance of a variety of other optimization algorithms.
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