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.

摘要：近期一项研究针对甘蔗收割作业阵线的规划与调度问题提出了优化模型。该问题属于复杂的农业物流问题，涵盖多项影响因素，包括原料成熟度、农业生产单元的收割作业、原料向糖厂的运输以及糖厂的制糖产能。本研究采用此前已被探讨过的一类优化模型，以带有序列相关调整时间与成本的并行机批量调度与规划混合整数规划（Mixed Integer Programming, MIP）模型对该问题进行建模。所提出的方法基于混合整数规划启发式算法，针对该行业典型企业的收割季实际场景求解该模型，其设计灵感来源于收割区块聚合启发式、松弛-固定构造启发式以及固定-优化改进启发式。为对比各启发式方法的性能，本研究采用这些方法的多种组合与变体开展了多组对比实验。其中三种方法可生成高质量解，本研究对其中一种方法进行了详细阐述与分析，其在甘蔗收割作业阵线的规划与调度决策方面展现出了颇具潜力的应用效果。