Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithm in Parameter Estimation of Nonlinear Dynamic Systems
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Controlling chaos by GA-based reinforcement learning neural network
IEEE Transactions on Neural Networks
Multi-criteria sequence-dependent job shop scheduling using genetic algorithms
Computers and Industrial Engineering
Real-time deterministic chaos control by means of selected evolutionary techniques
Engineering Applications of Artificial Intelligence
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Utilization of SOMA and differential evolution for robust stabilization of chaotic Logistic equation
Computers & Mathematics with Applications
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In this paper, we study an evolutionary algorithm employed to design and optimize a local control of chaos. In particular, we use a multi-objective fitness function, which consists of the objective function to be optimized and an auxiliary quantity applied as an additional driving force for the algorithm. Numerical results are presented illustrating the proposed scheme and showing the influence of employing such a multi-objective fitness function on convergence of the algorithm.