In this paper, we give a new approach of hybrid direct search methods with meta-heuristics of simulated annealing for finding a global minimum of a nonlinear function with continuous variables. First, we suggest a Simple Direct Search (SDS) method, which comes from some ideas of other well known direct search methods. Since our goal is to find global minima and the SDS method is still a local search method, we hybridize it with the standard simulated annealing to design a new method, called the Simplex Simulated Annealing (SSA) method, which is expected to have some ability to look for a global minimum. To obtain faster convergence, we first accelerate the cooling schedule in SSA, and in the final stage, we apply Kelley