Abstract: Using the population model and the chemical reaction model as examples, the experimental results of building the ordinary differential equation （ODE） models for dynamical systems by using fourteen kinds of algorithms which are based on two traditional searching methods （i.e. the local search algorithm and the simulated annealing algorithm）, genetic programming （GP）, genetic algorithm （GA） and their combinations are studied in detail. Some new conclusions about the comparisons of the performance of those algorithms are drawn at the end of this paper. The results of both examples show that of the fourteen kinds of algorithms the algorithm called GP+GA+LS MU is the best one in solving the modeling problem of ODE, which is performed by embedding a parameter optimization process using GA into the structure optimization process using GP, and adding local search for some individuals in the population at the end of each generation based on the standard GP mutation operators to generate their neighbor solutions.