Programming and scheduling sugarcane harvesting fronts: model and solution methods for large-scale problems

Abstract: In a recent study, optimization models were proposed for programming and scheduling sugarcane harvesting fronts. This is a complex agricultural and logistic problem comprising various factors, such as raw material maturation stage, harvesting at the agricultural unit, transporting of raw material to the plant, and milling capacities of the plant. In this study, one of the optimization models previously studied was used to represent this problem using Mixed Integer Programming (MIP) of a lot sizing and scheduling model in parallel machines with sequence dependent setup times and costs. The proposed methods are based on MIP heuristics to solve this model in a real situation of a harvest season of a typical company from this sector inspired by harvest block aggregation heuristics, relax-and-fix constructive heuristics, and fix-and-optimize improvement heuristics. To compare the performance of the heuristic methods, various experiments were conducted using different combinations and variations of these methods. Three approaches were able to produce good quality solutions. One of them is described in detail and analyzed in this study, showing promising results in terms of making programming and scheduling decisions concerning sugarcane harvesting fronts.