The buffer sizing problem in unreliable production lines is an important, indeed, complex combinatorial optimization problem with many industrial applications. These applications include quality, logistics and manufacturing production systems. In the formulation of the problem, the system consists of n machines, n fixed-size buffers and m inspection station in series. The objective is to minimize a combined storage and shortage costs, and also specifying the optimal location of inspection stations in the system. The present paper aims at optimizing a generalization of the model previously proposed in (Mhada et al., 2014) using a novel approach. In this approach, we combine Tabu Search (TS) and Genetic Algorithm (GA) to identify search regions with promising locations of inspection stations and an exact method to optimize the assignment of buffer sizes for each location. This approach provides a balance between diversification and intensification. Numerical results on test problems from previous research are reported. Using this approach, we can reduce the solution time by more than 97% in some cases.