Welcome to the InfoSci Platform
A Mixed Integer Programming Approach for Sugar Cane Cultivation and Harvest Planning

A Mixed Integer Programming Approach for Sugar Cane Cultivation and Harvest Planning

Sanjay Jena, Marcus Poggi de Aragão
Copyright: © 2011 |Pages: 31
ISBN13: 9781616928711|ISBN10: 1616928719|EISBN13: 9781616928735
DOI: 10.4018/978-1-61692-871-1.ch009
Cite Chapter Cite Chapter

MLA

Jena, Sanjay, and Marcus Poggi de Aragão. "A Mixed Integer Programming Approach for Sugar Cane Cultivation and Harvest Planning." Computational Methods for Agricultural Research: Advances and Applications, edited by Hércules Antonio do Prado, et al., IGI Global, 2011, pp. 144-174. https://doi.org/10.4018/978-1-61692-871-1.ch009

APA

Jena, S. & Poggi de Aragão, M. (2011). A Mixed Integer Programming Approach for Sugar Cane Cultivation and Harvest Planning. In H. do Prado, A. Barreto Luiz, & H. Filho (Eds.), Computational Methods for Agricultural Research: Advances and Applications (pp. 144-174). IGI Global. https://doi.org/10.4018/978-1-61692-871-1.ch009

Chicago

Jena, Sanjay, and Marcus Poggi de Aragão. "A Mixed Integer Programming Approach for Sugar Cane Cultivation and Harvest Planning." In Computational Methods for Agricultural Research: Advances and Applications, edited by Hércules Antonio do Prado, Alfredo Jose Barreto Luiz, and Homero Chaib Filho, 144-174. Hershey, PA: IGI Global, 2011. https://doi.org/10.4018/978-1-61692-871-1.ch009

Export Reference

Mendeley
Favorite

Abstract

The planning of agricultural cultivation and harvesting is a complex task. However, this area of study is still relatively young. This chapter focuses on the tactical and operational planning for sugar cane cultivation and harvesting which determines the best moment to harvest the fields, maximizing the total profit given by the sugar content within the cane. It considers resources such as cutting and transport crews, processing capacities in sugar cane mills, the use of maturation products and the application of vinasse on harvested fields. The mixed integer programming model extends the classical Packing formulation, adding a network flow structure to represent the harvest scheduling. All experiments were performed with real-world instances provided by a Brazilian sugar cane producer. The suggested solutions are discussed in terms of quality and use in practice.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.