Efficient Numerical Optimization Algorithm Based on Genetic Algorithm for Inverse Problem

We have developed an efficient algorithm based on the Genetic Algorithm(GA) for optimization of a model of a nonlinear system. Estimation of the interaction mechanisms among system components by using experimentally observed dynamic responses (timecourses) of some of the system components is generally referred to as “inverse problem”. The S-system, which belongs to power-law formalism, is one of the best representations to solve such an inverse problem; the S-system is rich enough in structure to capture all relevant dynamics. In this paper, for the purpose of solving the inverse problem, we introduce the GA and propose an efficient procedure for the estimation of large numbers of parameters in the S-system formalism. We applied our method to a simple oscillatory system and a gene expression network.