This paper addresses the optimization of the tactical planning for the Fast Moving Consumer Goods industry using an MILP model. To prevent unnecessary waste and missed sales, shelf-life restrictions are introduced using three methods. The direct method tracks the age of products directly. While it provides optimal solutions, it is computationally inefficient. The indirect method forces products to leave inventory before the end of their shelf-life. It obtains solutions within a few percent of optimality. Moreover, compared to the direct method, the computational time was on average reduced by a factor 32. The hybrid method models the shelf-life directly in the first and indirectly in the second storage stage. It obtains near optimal solutions and, on average, reduces the required computational time by a factor 5 compared to the direct method. Cases containing up to 25, 100, and 1000 SKUs were optimized using the direct, hybrid and indirect method respectively. (C) 2014 Elsevier Ltd. All rights reserved.