A bi-objective genetic approach for the selection of sugarcane varieties to comply with environmental and economic requirements

Florentino, Helenice de Oliveira; Pato, Margarida Vaz

doi:10.1057/jors.2013.21

Cited by 16 publications

(13 citation statements)

References 9 publications

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“…In view of the optimized scenario presented, the varieties SP 813250 and RB 835486 were selected, provided mathematical models using mixed integer programming for the tactical and operational planning of sugarcane harvesting. Oliveira Florentino and Pato [19] developed bi-objective optimization models for the selection of sugarcane varieties that meet environmental and economic requirements.…”

Section: Resultsmentioning

confidence: 99%

Optimization in the Selection of Sugarcane Varieties in a Sucro Energy Plant Located in the State of São Paulo, Brazil

Cervi¹,

Florentino²,

Filho³

et al. 2020

JAST-B

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Sugarcane crops have undergone several changes with the intensification of agricultural machinery in Brazil in the last years. This occurs, mainly, due to the transfer of the semi-mechanized system to the mechanized one during harvest operations. Thus, studies are needed on the optimization of sugarcane production in relation to mechanized processes, since it is necessary to verify the adaptability of sugarcane varieties to the mechanization of the plantation. This study aimed to develop and apply a mathematical model of optimization to select sugarcane varieties that maximize production and meet the quality standards required by the industry for sugar and fiber contents. The data were collected in a sugarcane mill located in the interior of Sã o Paulo state. The result obtained by the optimization process evinced an increase of 16.65% when compared to the productivity of the initial scenario.

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Section: Resultsmentioning

confidence: 99%

Optimization in the Selection of Sugarcane Varieties in a Sucro Energy Plant Located in the State of São Paulo, Brazil

Cervi¹,

Florentino²,

Filho³

et al. 2020

JAST-B

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“…En las SBSC las decisiones estratégicas de los diferentes eslabones tienen una relación de interdependencia. Por ejemplo, la capacidad de producción de la biorefinería depende del tamaño de los cultivos, la selección de variedades, las decisiones de inversión en terrenos agrícolas, ya sea a través de compra o alquiler, y de la demanda en la zona de influencia de los clientes (Sartori et al, 2001;de Oliveira Florentino & Pato, 2014;Carvajal et al, 2019). Las decisiones de localización de los cultivos y la biorefinería también inciden en la selección de equipos de cosecha y transporte y en su estrategia de adquisición.…”

Section: Decisiones Estratégicas Y Tácticas En Las Sbscunclassified

Biofuels technologies: An overview of feedstocks, processes, and technologies

Ziolkowska

2020

Biofuels for a More Sustainable Future

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“…In 2014, Florentino and Pato [5] presented a bi-objective binary linear programming model for sugarcane variety selection and harvesting residual biomass utilization. The computational experiment showed a high quality of the proposed multiobjective Genetic Algorithm and a low computational time.…”

Section: Mathematical Modelsmentioning

confidence: 99%

“…These studies present methodologies to optimize the sugarcane harvesting planning aiming to maximize sugarcane production; minimize costs related to harvesting; minimize the number of maneuvers of the harvester machine; optimize routes for the transport of machines and trucks and many others. The mathematical tools use continuous, discrete and heuristic optimization techniques [2][3][4][5][6][7].…”

Section: Introductionmentioning

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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A bi-objective genetic approach for the selection of sugarcane varieties to comply with environmental and economic requirements

Cited by 16 publications

References 9 publications

Optimization in the Selection of Sugarcane Varieties in a Sucro Energy Plant Located in the State of São Paulo, Brazil

Optimization in the Selection of Sugarcane Varieties in a Sucro Energy Plant Located in the State of São Paulo, Brazil

Biofuels technologies: An overview of feedstocks, processes, and technologies

Mathematical Optimization Models in the Sugarcane Harvesting Process

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