A multi-objective GA-simplex hybrid approach for gene regulatory network models

Genetic algorithms are exploratory search techniques that rely on a large population of individuals. In order to improve the search process, several hybrid approaches have been proposed that make use of a local exploitative search technique, such as the Nelder-Mead simplex algorithm. The simplex algorithm has been modified for multi-objective optimization, by introducing the concept of fuzzy dominance. A hybrid algorithm, the fuzzy dominance based simplex - genetic algorithm (FSGA) has been proposed. This algorithm was shown to be a very effective search strategy when applied to a multi-objective problem in modelling the gene regulatory network of flowering time control of Oryza sativa.