Abstract To guarantee acceptable hard candy quality during the cooling stage, the distribution of the product’s temperature throughout the cooling tunnel must be controlled. Hence, the product’s quality depends on the operating conditions of the cooling process and the air conditioning system. In this paper, hard candy quality, operating policies and production planning are integrated in an NLP optimization mathematical model to obtain optimal operating polices under different operating modes, minimizing the annual cost. The resulting model is applied in different case studies in which the production of one, and then six products, is analyzed considering different levels of production, demand and conveyor belt capacities. The study also considers different operating conditions for the air conditioning system under three possible operating modes during the year.