Multiobjective 0-1 integer programming for the use of sugarcane residual biomass in energy cogeneration

Florentino, Helenice de Oliveira; Lima, Adriano Dawison de; Carvalho, Lídia Raquel de; Balbo, Antônio Roberto; Homem, Thiago Pedro Donadon

doi:10.1111/j.1475-3995.2011.00818.x

Cited by 16 publications

(11 citation statements)

References 18 publications

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“…The main decisions to be made at the time of planting are related to: what is the best time to plant, which sugarcane varieties will be planted, and how to estimate what will be obtained when the plant is ready for harvest. Among the papers selected for this study, seven were found proposing mathematical optimization models to represent decisions associated with the planting time (Florentino and Sartori, 2003;Sartori and Florentino, 2007;Florentino et al, 2008;Colin, 2009;Florentino et al, 2011;Florentino and Pato, 2014;Lima et al, 2017). Florentino et al (2008Florentino et al ( , 2011, Florentino and Pato (2014), Lima et al (2017), and Sartori and Florentino (2007) present binary linear optimization models to select the varieties for planting.…”

Section: Plantingmentioning

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: Plantingmentioning

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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“…2020), quienes proponen modificaciones y ajustes en los procesos industriales para obtener mayores eficiencias en la producción de biocombustibles, reduciendo el nivel de emisiones equivalentes. De igual manera, algunos autores han propuesto incrementar la producción de biocombustibles y energía por cogeneración eléctrica del bagazo, considerando la recolección de la biomasa del campo (residuo de cosecha), así como el residuo de la caña de azúcar (luego de la extracción del jugo) (Mishoe et al, 1979;Sartori et al, 2001;de Oliveira Florentino & Pereira Sartori, 2003;De Oliveira Florentino et al, 2011;de Oliveira Florentino & Pato, 2014).…”

Section: Perspectiva Sostenible En Las Asc En La Caña De Azúcarunclassified

“…A través de información climática, el modelo propuesto en (Bezuidenhout & Singels, 2007b) fue testeado, también, se simulo la producción de los Con el objetivo de maximizar la producción de caña de azúcar, proponen un modelo de simulaciónoptimización el cual permite recomendar, variedad que se debe cultiva, fechas de siembra y cosecha para una temporada de cosecha De Oliveira Florentino et al (2011) x ---x ---p Proponen un modelo para la cogeneración de energía eléctrica usando residuos de la cosecha de caña de azúcar; encontrando un plan de cosecha que balancea el costo de la energía requerida y la generada x ----x x x p Desde la perspectiva sostenible, los autores proponen un modelo para la evaluación de la SC de biocombustibles. No considera aspectos de la ASC de Oliveira Florentino et al (2018) x x -x x x --v Proponen un modelo de optimización y una metaheurística para programar la cosecha, considerando el periodo de maduración y la fecha de siembra, así como, los intereses del ingenio…”

Section: Modelounclassified

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

Ziolkowska

2020

Biofuels for a More Sustainable Future

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“…Some authors, like those of reference [25], propose a multi-objective integer linear programming optimization model to choose sugarcane varieties to minimize costs in the use of crop residue and simultaneously maximize the energy balance in such a process. In that paper, the authors considered different logistics costs.…”

Section: Literature Review-bioenergy Supply Chain Optimizationmentioning

confidence: 99%

Supply Chain Optimization for Energy Cogeneration Using Sugarcane Crop Residues (SCR)

Manyoma-Velásquez¹,

Manotas-Duque²

2019

Sustainability

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Access to clean and non-polluting energy has been defined as a Sustainable Development Goal (SDG). In this context, countries such as Colombia have promoted policies and incentives for the implementation of energy projects with non-conventional sources of energy. One of the main energy alternatives available is related to the use of residual biomass left by agribusiness supply chains, such as sugarcane. In Colombia, sugar cane is grown and harvested all year round, due to the local tropical climate. The model we propose addresses the question of the selection of the plots whose crop residue will be transported for energy production on a given day. We built a Mixed-Integer Programming model to decide which plots to harvest on a given day. Although no additional energy is generated in the model, the results show that it is feasible to replace all coal used in the boilers with sugarcane crop residues (SCRs) for power cogeneration. Sustainability 2019, 11, 6565 2 of 15The use of agricultural crop residues in electrical co-generation processes has been widely discussed in the literature. Some authors, such as those of reference [3], systematically describe energy needs and targets, biofuel feedstocks, conversion processes, and provide a comprehensive review of biomass supply chain (BSC) design and modeling. In reference [4], the authors describe the key challenges and opportunities in the modeling and optimization of biomass-to-bioenergy supply chains. The optimization process of a biomass supply chain is essential to overcome barriers and uncertainties that may inhibit the development of a sustainable and competitive bioenergy market. In reference [5], the authors give an overview of the optimization techniques and models, focusing on decisions regarding the design and management of the upstream segment of the biomass-for-bioenergy supply chain. Another research approach is related to the integration of different optimization objectives in biomass supply chain models. There is a recent tendency to integrate economic, environmental, and social aspects in the evaluation and optimization of biomass supply chains. Some authors (for example, those of reference [6]) have reviewed the studies that assessed or optimized economic, social, and environmental aspects of forest biomass supply chains for the production of bioenergy and bio-products.The structure of this paper is as follows: In Section 1.2, we present a literature review of bioenergy supply chain optimization decisions. In Section 2, the optimization model is explained, taking into account the parameters, variables, objective functions, and constraints. Sections 3 and 4 present the results and discussion. Section 5 presents conclusions and future research options. The Julia code of the model is included as an appendix.

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Multiobjective 0-1 integer programming for the use of sugarcane residual biomass in energy cogeneration

Cited by 16 publications

References 18 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

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

Supply Chain Optimization for Energy Cogeneration Using Sugarcane Crop Residues (SCR)

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