The effect of placing a stationary airfoil downstream of a pitching airfoil in a tandem configuration was investigated using computational fluid dynamics. A finite-volume URANS solver was employed to simulate the flow field. An optimization study was performed at the low Reynolds number of 30,000 for SD7003 airfoils using a genetic algorithm. Three artificial neural networks were coupled with the genetic algorithm to reduce the computational cost. The optimization process was used to find the optimum design parameters in order to maximize lift to drag ratio of airfoils together in addition to the thrust coefficient of the hindfoil. It was found that a significant improvement of 174% and 15% could be achieved for the thrust coefficient of static hindfoil and L/D of the combined airfoils respectively in tandem configuration over single airfoils at optimum values of design parameters.