The quality of food products deteriorates continuously over time at a speed depending on the storage temper-ature. Therefore, they must be stored at low temperatures to prolong their shelf life, which increases storage costs significantly. In this paper, we study a distribution problem in which a temperature-controlled warehouse is responsible for supplying a perishable food product, using a homogenous fleet of capacitated vehicles, to mul-tiple customers with minimum quality requirements and delivery time windows. The objective is to minimize the sum of the energy cost at the warehouse and the transportation cost to deliver the customer demand. Decisions include the storage temperature at the warehouse and delivery routes. The distribution problem is formulated as a Mixed-Integer Linear Programming (MILP) model. After presenting an analytical study of the problem, a heuristic based on General Variable Neighborhood Search (GVNS) is designed to solve the large-size problem instances. Using the case of a dairy product, the model is solved under various scenarios. It is observed that the distribution and temperature decisions are dependent. Moreover, the optimal distribution plan and storage temperature are significantly impacted by changes in factors related to food quality, such as truck and envi-ronmental temperatures and energy price.