A periodic-review inventory model with nonstationary stochastic demand under an (s, S) policy is considered. We apply a genetic algorithm to solve for reorder points and order-up-to levels which minimize an expected total cost. A closed-form exact expression for the expected cost is obtained from a nonstationary discrete-time Markov chain. In our numerical experiments, our approach performs very well.