Abstract
Hybrid algorithms that combine genetic algorithms with the Nelder-Mead simplex algorithm have been effective in solving certain optimization problems. In this article, we apply a similar technique to estimate the parameters of a gene regulatory network for flowering time control in rice. The algorithm minimizes the difference between the model behavior and real world data. Because of the nature of the data, a multi-objective approach is necessary. The concept of fuzzy dominance is introduced, and a multi-objective simplex algorithm based on this concept is proposed as a part of the hybrid approach. Results suggest that the proposed method performs well in estimating the model parameters.
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Koduru, P., Das, S., Welch, S., Roe, J.L. (2004). Fuzzy Dominance Based Multi-objective GA-Simplex Hybrid Algorithms Applied to Gene Network Models. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24854-5_37
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DOI: https://doi.org/10.1007/978-3-540-24854-5_37
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