A novel hybrid immune algorithm for global optimization in design and manufacturing
Robotics and Computer-Integrated Manufacturing
Using a hybrid genetic algorithm and fuzzy logic for metabolic modeling
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
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The Genetic Algorithm is applied to the parameter estimation problem to optimize a model of the glucose cycle of an E. coli cell. Since the evaluation of the model is computationally expensive, a hybrid algorithm is proposed which grafts a proposed variant of Nelder and Mead' s downhill simplex-called Concur- rent Simplex-with the Genetic Algorithm by using the simplex as an additional operator. The addition of the operator speeds up the rate of convergence of the Genetic Algorithm in some cases. The advantages and disadvantages of the simplex hybrid are discussed and the hybrid is tested against several different problem sets to verify its improvement over the generic genetic algorithm.