An optimization model for combined selecting, planting and harvesting sugarcane varieties

The problem of selecting sugarcane varieties has been widely discussed due to its computational complexity and its great impact for the sugar and ethanol industry. This paper proposes a new integrated mathematical programming model to deal with the selection of sugarcane varieties to be planted and the determination of the optimal period for planting and harvesting in order to increase production in the sugarcane industry. The proposed model optimizes the production of sugarcane and improves the quality of biomass whilst satisfying the main constraints imposed by sugarcane companies. The problem is modelled as an integer linear program (ILP) and solved using an exact method to generate optimal solutions for small and medium problems. For large problems, metaheuristic approaches based on Genetic Algorithm (GA) and Variable Neighbourhood Search (VNS) are proposed. According to the results, the proposed methodology provides sugarcane company managers with decision support in selecting the most suitable varieties and in determining the best period to plant and harvest their sugarcane.