Adaptive Zooming Genetic Algorithm for Continuous Optimisation Problems
نویسندگان
چکیده
This paper proposes an adaptive zooming genetic algorithm (AZGA) for continuous optimisation problems. Other than gradually reducing the search space with a fixed reduction rate during the evolution process, the upper and lower boundaries for variables in the objective function are dynamically adjusted based on the distribution information of variables in the whole population. This technique is evaluated on a suite of benchmark test functions to confirm its effectiveness over existing techniques in terms of convergence speed and robustness. Copyright © 2005 IFAC
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