Abstract
In this paper, we present a novel mixed integer linear programming (MIP) model to solve the problem of storage space optimization in a port grain cereal silo. This work is based on a real case study for scheduling storage operations in a port cereal silo, where schedulers are faced daily with the problem of finding the best solution for transfers between storage cells, to maximize the number of empty cells, in order to have greater capacity to receive new lots, subject to storage and transportation lines capacity constraints, and receiving dispatching plans. The problem is formulated by a mixed integer linear programming model and implemented in an Excel/VBA platform. The results show that the model optimizes the number of empty cells, in computational time less than 60 seconds, and thereby constitutes a significant added value to the concerned company. © 2015 Taylor & Francis Group, London.