Harvest planning in the Brazilian sugar cane industry via mixed integer programming

Jena, Sanjay Dominik; Poggi, Marcus

doi:10.1016/j.ejor.2013.04.011

Cited by 70 publications

(45 citation statements)

References 9 publications

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“…Analyzing the models related to sugarcane harvesting and transportation planning available in the literature, it was observed that although the studies carried out by Higgins (1999), Higgins & Muchow (2003), Higgins et al (2004), Grunow et al (2007), and Jena & Poggi (2013) address many aspects of the situation-problem using GAP -Generalized Atribution Problem, planting and harvesting are addressed without examining the harvest front shifts. The discussions are based on previous concepts of harvest fronts without considering harvest block scheduling, reduction in the production capacity due to the harvest front shifts, and the impact of these shifts on harvesting and transport capacity.…”

Section: Research Gapmentioning

confidence: 99%

“…Some computational tools available in the market and in literature focus on the following planning and control models: sugarcane field reform planning (Barata, 1992;Higgins, 1999), crop planting planning (Sartori et al, 2001) harvesting planning (Barata, 1992;Grunow et al, 2007;Jena & Poggi, 2013) operational planning (Grunow et al, 2007;Jena & Poggi, 2013), and traffic control (Hahn & Ribeiro, 1999). However, there are few studies available in the literature addressing programming and scheduling of sugarcane harvest fronts (Junqueira, 2014).…”

Section: Introductionmentioning

confidence: 99%

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

Junqueira

Morábito

2017

Gest. Prod.

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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.

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Section: Research Gapmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Junqueira

Morábito

2017

Gest. Prod.

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“…The results showed an improvement average of 16.38% in sugar production. Jena and Poggi [8] presented an optimization model for tactical and operational planning such that the total sugar content in the harvested sugarcane is maximized. The model was solved using heuristic techniques and approached Lagrangian relaxation or Benders decomposition.…”

Section: Mathematical Modelsmentioning

confidence: 99%

Mathematical Optimization Models in the Sugarcane Harvesting Process

Doriguel¹,

Crusciol²,

Florentino³

2018

Sugarcane - Technology and Research

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Over the past few decades, due to environmental and economic factors, the sugarcane has been considered a versatile and important plant to the several countries. The energysugar-ethanol agro-industries are seeking to take advantage of all its material, with the main products produced being renewable energy, sugar and ethanol. In this chapter, we propose to present a review of the important works that use mathematical and computational tools, aiming to optimize the sugarcane harvesting, in the past 30 years.

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“…Various studies have addressed planning sugarcane harvesting, such as: Higgins et al (1998Higgins et al ( , 2004a, Higgins (1999Higgins ( , 2002 and Higgins & Muchow (2003) in the Australian context; Grunow et al (2007) in the Venezuelan context and Jena & Poggi (2013) in the Brazilian context. However, these studies either disregard the division into harvesting fronts or predefine it by harvest blocks.…”

Section: Introductionmentioning

confidence: 99%

“…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. In parallel, heuristic methods based on MIP, such as relax-and-fix, presented by Pochet & Wolsey (2006) and fix-and-optimize, proposed by Helber & Sahling (2010), have been widely used to solve the large scale General Lotsizing and Scheduling Problem for Parallel Production Lines, as shown for example in Beraldi et al (2008), Ferreira et al (2009Ferreira et al ( , 2012, Toso et al (2009) and Helber & Sahling (2010).…”

Section: Introductionmentioning

confidence: 99%

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

Junqueira

Morábito

2017

Gest. Prod.

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Palavras-chave: Programação de colheita de cana-de-açúcar; Dimensionamento e sequenciamento de lotes de produção; Programação inteira mista; Heurísticas relax-and-fix e fix-and-optimize.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.

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Harvest planning in the Brazilian sugar cane industry via mixed integer programming

Cited by 70 publications

References 9 publications

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

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

Mathematical Optimization Models in the Sugarcane Harvesting Process

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

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