The world meat market demands competitiveness and optimal livestock replacement decisions can help to achieve this goal. We introduce a novel discrete stochastic dynamic programming framework to support a manager’s decision-making process of whether to sell or keep fattening animals in the beef sector. In particular, our proposal uses a non-convex value function, combining both economic and biological variables, and involving uncertainty with regard to price fluctuations. Our methodology is very general, so practitioners can apply it in different regions around the world. We illustrate the model’s convenience with an empirical application, finding that our methodology generates better results than actions based on empirical experience.
