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Abstract: One of the main obstacles in applying genetic algorithms (GAs) to complex problems has been the high computational cost due to their slow convergence rate. We encountered such a difficulty in an attempt to use the classical GA for estimating parameters of a metabolic model. To alleviate this difficulty, we developed a hybrid approach that combines GA with a stochastic variant of the simplex method in function optimization. Our motivation for developing the stochastic simplex method is to... (Update)
Context of citations to this paper: More
...Leardi, R. 290, 430] LeBaron, B. 125] Lebedko, O. A. 149] Leblebicioglu, K. 479] Lecce, L. 16] Lee, B. 843] Lee, Bogju, [282, 287] Lee, Chang Yong, 158] Lee, Ho Kyung, 225] Lee, Hong Bae, 472] Lee, In Beum, 225] Lee, J. 68] Lee, K. K. 262] Lee, K. Y....
.... a binary GA followed by a Levenberg Marquardt optimization, for the estimation of kinetic parameters of a chemical reaction [8] Yen et al. [19] used a hybrid GA simplex method to solve the parameters in a dynamic metabolic model. Here we propose a real coded GA [7] for the...
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BibTeX entry: (Update)
J. Yen, J. C. Liao, D. Randolph, and B. Lee, "A hybrid approach to modeling metabolic systems using genetic algorithm and simplex method," In Proceedings of the 11th IEEE Conference on Artificial Intelligence for Applications (CAIA95), pp. 277--283, Los Angeles, CA, Feburary 1995. http://citeseer.ist.psu.edu/yen95hybrid.html More
@inproceedings{ yenhybrid,
author = "J. Yen and J. Liao and D. Randolph and B. Lee",
title = "A Hybrid Approach to Modeling Metabolic Systems Using Genetic Algorithms and the Simplex Method",
pages = "277--285",
url = "citeseer.ist.psu.edu/yen95hybrid.html" }
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