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

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 multiobjective 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. 1 Gene Regulatory Network Models Molecular geneticists are rapidly deciphering the genomes of an increasing number of organisms. As of November 2003, 166 organisms had completely sequenced genomes with another 775 in progress [1]. The current challenge is to understand how the genes in each organism int...

• Type: Conference
• Year: 2004
• Where: GECCO
• Authors: Praveen Koduru, Sanjoy Das, Stephen Welch, Judith L. Roe
• Keywords: GECCO 2004, Gene Regulatory Network, Nelder-Mead Simplex Algorithm, Simplex Algorithm