Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Journal of Global Optimization
Advances in Differential Evolution
Advances in Differential Evolution
ISDA '09 Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
JADE: adaptive differential evolution with optional external archive
IEEE Transactions on Evolutionary Computation
A Field Guide to Genetic Programming
A Field Guide to Genetic Programming
Adaptive Differential Evolution Based on New Mutation Strategy
ICCIS '11 Proceedings of the 2011 International Conference on Computational and Information Sciences
Extending particle swarm optimisation via genetic programming
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
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Genetic Programming (GP) is presented as an approach for the automatic generation of high quality mutation strategies for the Differential Evolution (DE) algorithm. To evaluate the generated mutation strategies, some well known continuous global optimization problems were selected. Also, a multi-layer perceptron neural network was trained for regression and classification tasks. Statistical analysis of the results showed quite satisfactory performance of the discovered mutation strategy (dubbed ADAM), presenting competitive or better results than classical mutation strategies. The contribution of this work is to show that GP is a potential tool for exploring new ideas in metaheuristics development, allowing for an automatic generation of mutation strategies that can present fast performance and high quality solutions.