Motivated by the heat-treating process in a launch vehicles manufacturing plant, we study a two-stage scheduling problem with limited waiting time where the first stage is a batch processor and the second stage is a discrete machine. A mixed-integer programming model is developed and two lower bounds are derived to measure the performance of proposed algorithms. An efficient heuristic together with worst-case analysis is also proposed. Genetic Programming approaches are applied to the flow-shop scheduling problem. Numerical results demonstrate that the proposed algorithms perform better than other meta-heuristics in different production scenarios.