论文信息 - Using Adaptive Operators in Genetic Search

Using Adaptive Operators in Genetic Search

In this paper, we provided an extension of our previous work on adaptive genetic algorithm [1]. Each individual encodes the probability (rate) of its genetic operators. In every generation, each individual is modified by only one operator. This operator is selected according to its encoded rates. The rates are updated according to the performance achieved by the offspring (compared to its parents) and a random learning rate. The proposed approach is augmented with a simple transposition operator and tested on a number of benchmark functions.

Fabio A. González | Jonatan Gómez | Dipankar Dasgupta

[1] Konstantinos G. Margaritis,et al. An Experimental Study of Benchmarking Functions for Genetic Algorithms , 2002, Int. J. Comput. Math..

[2] Bryant A. Julstrom,et al. What Have You Done for Me Lately? Adapting Operator Probabilities in a Steady-State Genetic Algorithm , 1995, ICGA.

[3] Peter Ross,et al. Adapting Operator Settings in Genetic Algorithms , 1998, Evolutionary Computation.

[4] Erik D. Goodman,et al. On the Application of Cohort-Driven Operators to Continuous Optimization Problems Using Evolutionary Computation , 1998, Evolutionary Programming.

[5] Lawrence Davis,et al. Adapting Operator Probabilities in Genetic Algorithms , 1989, ICGA.

[6] Jonatan Gómez,et al. Using Competitive Operators and a Local Selection Scheme in Genetic Search , 2002, GECCO Late Breaking Papers.