Abordagens de otimização para a programação e sequenciamento das frentes de colheita de cana-de-açúcar

Abstract

Resumo: A produção de açúcar, álcool e energia elétrica a partir de cana-de-açúcar passa necessariamente pela Abstract:The production of sugar, ethanol, and electricity from sugarcane necessarily involves harvesting and transportation of raw materials, which are expensive and complex operations that affect industrial efficiency. The present study proposes optimization approaches to support programming and scheduling harvest front decisions, based on considering the representation of the lot sizing and scheduling problem on parallel machines with sequence-dependent setup times and costs, a modeling technique widely reported in the literature. We carried out real data experiments in order to verify the adequacy and consistency of this representation. The results show that the proposed approaches adequately represent the conceptual model studied and have great potential to reduce cost in real-life situations.

Programação e sequenciamento das frentes de colheita de cana-de-açúcar: modelo e métodos de solução para problemas de grande porte

“…The latter is a critical factor for integrating the agricultural and industrial processes. According to Junqueira & Morabito (2017), part of this complexity is due to dividing the agricultural operation into various harvesting fronts, as well as the difficulties of programming and scheduling these fronts over time in order to maintain an average transport capacity of sugarcane for the plant, as the fronts change harvest blocks. Maintaining this average transport capacity could become unfeasible if all the harvesting effort were concentrated only in some points (for example, all fronts are located in only one harvest block) because either resources could be in excess (if most of these fronts are located too near the plant) or there could be a lack if the fronts were too far away.…”

“…However, these studies either disregard the division into harvesting fronts or predefine it by harvest blocks. In a previous study, Junqueira & Morabito (2017) were inspired by the General Lotsizing and Scheduling Problem for Parallel Production Lines (GLSPPL) proposed by Meyr (2002) and Meyr & Mann (2013), which presents three models concerned with planning sugarcane harvesting considering harvesting fronts. According to the analogy used by the authors, the harvest blocks are represented by the GLSPPL lots, whereas the harvesting fronts are represented by the production lines.…”

“…In contrast with other studies that predominantly use sucrose content estimates to assess the ripeness of the sugarcane planted which indicates the optimal harvesting period for an area, Junqueira & Morabito (2017) considered the Length of Time of Industrial Use (LTIU) for each harvesting block to determine the time-window at which a given area could be best harvested. Although they are interesting indicators for the expected income of the raw material, the sucrose content estimates may not be repeated in the next harvest due to: climate variations, soil fertilization, pest problems, diseases, as well as other biological factors that could affect the plant's behavior.…”

“…The models presented in Junqueira & Morabito (2017) also take into account the harvest potential and the transport variable per harvest block. Characteristics such as the expected productivity of the crop (tons per ha), the planting distance and number of maneuvers vary, depending on the area, and directly affect the hourly production rate of harvesting machines.…”

“…Despite the fact that this approach seems promising, Junqueira & Morabito (2017) solved the problem only for small samples, with few hundreds of constraints and variables, and dozens of these discrete variables. In order to address the actual sugarcane harvesting planning, Higgins et al (2004b), Higgins & Laredo (2006), as well as Jena & Poggi (2013) proposed methods that aggregate harvest blocks in order to reduce the number of variables involved.…”