Fuzzy Dominance Based Multi-objective GA-Simplex Hybrid Algorithms Applied to Gene Network Models

Praveen Koduru¹, Sanjoy Das¹, Stephen Welch², and Judith L. Roe³

¹Electrical and Computer Engineering

²Department of Agronomy

³Division of Biology, Kansas State University, Manhattan, KS 66506

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.

LNCS 3102, p. 356 ff.

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