Modeling and solving a sugarcane harvest front scheduling problem

Junqueira, Rogério de Ávila Ribeiro; Morábito, Reinaldo

doi:10.1016/j.ijpe.2019.03.009

Cited by 46 publications

(23 citation statements)

References 38 publications

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“…The daily transport schedules should combine farms from different distance zones in a way that ensures a steady inflow to the slaughterhouse throughout the day. Similar types of constraints also appear in other agricultural settings and there are alternative ways to cope with such constraint, see for example Junqueira and Morabito (2019) in the sugarcane harvest front scheduling problem in sugarmill supply logistics.…”

Section: Catching Teams and The Slaughterhousementioning

confidence: 84%

Optimisation of the broiler production supply chain

Brevik

Lauen

Rolke

et al. 2020

International Journal of Production Research

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In this paper, we propose a mixed integer programming (MIP) model for the Chicken Flock Sizing, Allocation and Scheduling Problem (CFSASP), which is an important planning problem in the broiler production supply chain. To solve the CFSASP efficiently, two variants of rolling horizon heuristics (RHHs) have been developed and applied on the case of a Norwegian broiler production company. Computational results show that the RHHs successfully obtain high-quality solutions within a reasonable time. The value of optimisation is verified through comparison with the case company's plans, where the solutions from optimisation outperforms the current solutions. Sensitivity analyses are also conducted to provide managerial insights regarding certain strategic decisions, such as how many and which days to use for hatching of chickens. Due to the promising results, the case company is now implementing an optimisation-based decision support system based on the MIP model and solution methods shown in this paper.

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Section: Catching Teams and The Slaughterhousementioning

confidence: 84%

Optimisation of the broiler production supply chain

Brevik

Lauen

Rolke

et al. 2020

International Journal of Production Research

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“…A sugarcane harvest front is made of a team that operates machinery and equipment with prior planning (Pongpat et al 2017 ). It includes sugarcane harvesters, transshipments (which accompany the harvesters to load the raw material) and the team that provides fuel supply, maintenance equipment, support for emergency services (fire) and trucks for transporting the harvested sugarcane to the mill (Junqueira and Morabito 2019 ).…”

Section: Discussionmentioning

confidence: 99%

“…The sugarcane delivery time (h) requires that the activities of harvesting and transporting the sugarcane to the industrial unit are made of complex logistical operations (Junqueira and Morabito 2019 ), with the transport of sugarcane being one important element of the production system (Masoud et al 2012 ). It requires planning to ensure efficient logistical activities (Zacura Filho and Piccirilli, 2012 ), because it is necessary to minimize the time between harvesting and processing at the mill (Junqueira and Morabito 2019 ), as the sugarcane harvested mechanically must be transported to the mills within a maximum of 24 h (Pongpat et al 2017 ).…”

Section: Discussionmentioning

confidence: 99%

Environmental, field and impurity factors to increase the agricultural performance of Brazilian and Australian sugarcane mills

Carlucci

Lemos

Salgado

et al. 2021

Clean Techn Environ Policy

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Graphic abstract This study aims to identify explanatory factors to increase the agricultural performance of Brazilian and Australian sugarcane mills. The relevance of Brazil and Australia for the sugar industry motivated the development this study based on the most important factors in both countries responsible for increasing the efficiency in sugarcane production. Thus, this study is designed to assess the hypothesis that there are a few explanatory variables that are deeply responsible for the agricultural efficiency in the sugar-energy sector. As a specific objective, it proposes a DEA (Data Envelopment Analysis) model that seeks to optimize the production of Total Recoverable Sugar (TRS) by planted area, and simultaneously, minimizes mineral and vegetable impurities. The sample consists of 82 observations from 32 sugarcane mills. An agricultural efficiency study was performed using the two-stage DEA, in which the evaluated mills according to the level of efficiency in the proposed model. Then, a Multiple Linear Regression Analysis was performed to identify the variables with the greatest influence on the performance of the mills in terms of efficiency. The results revealed six relevant variables for increasing the agricultural performance in the production of sugarcane: rainfall (mm weekly), chopped cane delivery (%), delivery time (h), borer (%), air humidity (%), and rods in raw wine (× 10 5 /mL). Finally, semi-structured interviews with Brazilian and Australian experts in the sugar-energy sector allowed the identification of five other relevant complementary factors that were unavailable in the database: genetic variety, agricultural cultivation activities, edaphoclimatic factors, renewal of sugarcane fields and irrigation system. The results of this study were grouped into the dimensions of environment, yield, and impurities, providing quantification and better understanding of the identified explanatory factors and the agricultural performance in terms of production efficiency, offering fundamental information that enables managers to make decisions and prioritize the aspects that contribute more significantly to the increase in agricultural productivity of the planted area.

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“…For instance, Grunow et al (2007) developed a hierarchical decision framework for the sugarcane supply problem in Venezuela, where the whole problem was decomposed into three decision stages, namely (i) cultivation planning, (ii) harvest scheduling, and (iii) resource dispatching, while Paiva and Morabito (2009) integrated the production of sugar, ethanol, and molasses into one single framework and modeled the resulting sugarcane supply chain problem with mathematical programming. Lamsal, Jones, and Thomas (2016) and Junqueira and Morabito (2019), on the contrary, focused more on the operational issues of sugar supply chains in two different geographic locations. In particular, Lamsal et al (2016) explored the logistics of harvested sugarcane in the United States so that the fleet size of trucks required for transportation was minimized, while Junqueira and Morabito (2019) investigated a socalled Harvest Front Scheduling Problem (HFSP) that combined harvesting and resource scheduling into one decision-making framework.…”

Section: Related Literaturementioning

confidence: 99%