Continuous Periods for Harvesting Schedules: A Numerical Application for the Brazilian Sugarcane Industry

Caixeta-Filho, José Vicente; Miyashita, André Eidi

doi:10.1590/0101-7438.2018.038.03.0535

Cited by 3 publications

(3 citation statements)

References 14 publications

(5 reference statements)

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“…The total recoverable sugar in sugarcane over time describes a bell curve with peak maturity occurring at the top of the curve. The objective is that the harvest is always performed at peak maturity, however, the time when it occurs may not coincide with the mill capacities, especially if many farms are harvested simultaneously (Caixeta‐Filho and Miyashita, 2018; Florentino et al., 2018). Therefore, a continuous effort is required to ensure the best utilization of the production, taking into account technical limitations and the needs of the mill.…”

Section: Analysis and Discussion Of The Selected Papersmentioning

confidence: 99%

A review of mathematical optimization models applied to the sugarcane supply chain

Teixeira¹,

Rangel²,

Florentino³

et al. 2021

Int Trans Operational Res

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Sugarcane is a product of great economic relevance and, as well as its use for the production of different types of sugar, it is also a renewable source for the production of bio‐fuels, other bio‐products, and electricity. In this context, efficient planning and technology changes are necessary to ensure high productivity, competitiveness and harmony with economic, social, and environmental issues. Consequently, this sector needs technical and scientific support. Mathematical optimization models can be useful to build efficient planning tools for the activities involved in the sugarcane supply chain, helping to address these challenges. This paper describes the sugarcane supply chain and presents a literature review of mathematical optimization models that have been proposed to represent its main stages: planting, harvesting, transporting, industrial processing, and marketing. The findings show that several models have been proposed to represent these five stages, however, most of them have not been thoroughly explored from the point of view of strength of the models and solution methods. Moreover, the harvesting stage is the one that has received more attention than the other stages. In the integration of two or more stages, there are many challenges yet to be addressed by mathematical optimization models. This review contributes to a better understanding of the sugar‐energy sector and opens up new perspectives for future investigations.

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Section: Analysis and Discussion Of The Selected Papersmentioning

confidence: 99%

A review of mathematical optimization models applied to the sugarcane supply chain

Teixeira¹,

Rangel²,

Florentino³

et al. 2021

Int Trans Operational Res

View full text Add to dashboard Cite

show abstract

“…A programação linear é um aperfeiçoamento da técnica de resolução de sistemas de equações lineares via inversões sucessivas de matrizes, com a vantagem de incorporar uma equação linear adicional que exprime um comportamento que deve ser sincronizado (Caixeta Filho, 2004).…”

Section: 'Pesquisa Operacionalunclassified

Tomada de decisão para alocação de volume de prestadores de serviços de transporte rodoviário e armazenagem alfandegada

Cavalcante da Silva,

Da Paz,

Souza

et al. 2023

ENIAC

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Com o avanço da globalização e o crescimento do mercado internacional, empresas têm buscado a redução de custos, melhoria no desempenho logístico, e maior competividade. O objetivo desse artigo foi otimizar os custos na movimentação de contêineres numa operação logística de transportes rodoviários e armazenagem alfandegada nas operações de importação marítima a partir do Porto de Santos. A metodologia aplicada foi uma pesquisa exploratória quantitativa, seguida de um estudo de caso único em uma empresa varejista importadora. Utilizou-se o software Lindo 6.1 para formulação e resolução do modelo de programação linear a fim de otimizar a redução dos custos dentre as alternativas envolvidas nas operações inbound da empresa estudada. Dentre os resultados, foi possível verificar que o modelo de programação linear, permitiu uma redução do custo logístico em 3%, quando comparado com os custos operacionais obtidos atualmente pela empresa estudada além de orientar para otimização e melhor alocação de volumes para os prestadores de serviço de transporte rodoviário e armazenagem alfandegada

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“…Pode-se notar, com base nas definições acima, que os modelos podem ser um protótipo, uma representação simplificada, bem como uma abstração de uma realidade (DOURADO NETO et.al, 1998). Modelos são representações teóricas para situações reais (CAIXETA FILHO, 2001), e tem por premissa que o estado de um sistema, assim como suas possíveis variações, podem ser quantificados e caracterizados a qualquer momento por equações matemáticas (DE WIT; GOUDRIAAN, 1974).…”

Section: Modelagem Matemática E Seu Uso Na Agriculturaunclassified

Modelagem da maturação da cana-de-açúcar em função de variáveis meteorológicas

Cardozo¹

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Modeling sugarcane ripening as a function of meteorological variables The effect of meteorological variables on sugarcane ripening is a not very well known process in spite of the several impacts of that on the quality of the raw material for the sugarcane industry. The objective of this study was to evaluate the effects of meteorological variables on sugarcane ripening and based on that to establish models able to describe this process. The study was conducted in an area of the Raízen Group (former Cosan), in Piracicaba, state of São Paulo, Brazil, from March 2002 (planting) to October 2003. Eight sugarcane cultivars were evaluated by analyzing 32 samples collected from March to October 2003. Variables related to the quality of the raw material (ATR, AR, ART, Purity, Brix, Pol%cane, fiber and moisture) and weather (air temperature, rainfall, solar radiation, among others) were submitted to descriptive and multivariate statistical analysis in order to better understand the sugarcane ripening process and the relationship between this process and environmental conditions. The meteorological variables of best fit were used for elaborating the models to describe the ripening process, which were grouped into early, middle and late, according to the maturity pattern of the studied cultivars. The evaluation of the models was based on the analysis of residuals (presence of outliers, homogeneity of variances and normality of residuals) and on the comparison between estimated and independent data (mean errors, R 2 , agreement index of Willmott and confidence index of Camargo). Regardless of the pattern of sugarcane maturation (early, middle and late), the models that presented the best performance were for ATR, Brix, Pol% cane and humidity variables, with adjusted R 2 values above 0.9 (p significant at 1%) and excellent performance, with C index above 0.85, when evaluated with independent data. The fiber model had the lowest adjusted R 2 values (around 0.65) and problems in the distribution of its residuals (non-normality); however, when it was tested with independent data an acceptable performance was found, with C index above 0.8. The generated models showed that precipitation can be used as the main variable for predicting sugarcane quality and that its use can be extended to other areas than the one where it was originally generated.

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Continuous Periods for Harvesting Schedules: A Numerical Application for the Brazilian Sugarcane Industry

Cited by 3 publications

References 14 publications

A review of mathematical optimization models applied to the sugarcane supply chain

A review of mathematical optimization models applied to the sugarcane supply chain

Tomada de decisão para alocação de volume de prestadores de serviços de transporte rodoviário e armazenagem alfandegada

Modelagem da maturação da cana-de-açúcar em função de variáveis meteorológicas

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