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A Linear Optimization Approach for Increasing Sustainability in Vegetable Crop Production

A Linear Optimization Approach for Increasing Sustainability in Vegetable Crop Production

Lana dos Santos, Marcos Arenales, Alysson Costa, Ricardo Santos
ISBN13: 9781616928711|ISBN10: 1616928719|EISBN13: 9781616928735
DOI: 10.4018/978-1-61692-871-1.ch012
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MLA

dos Santos, Lana, et al. "A Linear Optimization Approach for Increasing Sustainability in Vegetable Crop Production." Computational Methods for Agricultural Research: Advances and Applications, edited by Hércules Antonio do Prado, et al., IGI Global, 2011, pp. 234-265. https://doi.org/10.4018/978-1-61692-871-1.ch012

APA

dos Santos, L., Arenales, M., Costa, A., & Santos, R. (2011). A Linear Optimization Approach for Increasing Sustainability in Vegetable Crop Production. In H. do Prado, A. Barreto Luiz, & H. Filho (Eds.), Computational Methods for Agricultural Research: Advances and Applications (pp. 234-265). IGI Global. https://doi.org/10.4018/978-1-61692-871-1.ch012

Chicago

dos Santos, Lana, et al. "A Linear Optimization Approach for Increasing Sustainability in Vegetable Crop Production." In Computational Methods for Agricultural Research: Advances and Applications, edited by Hércules Antonio do Prado, Alfredo Jose Barreto Luiz, and Homero Chaib Filho, 234-265. Hershey, PA: IGI Global, 2011. https://doi.org/10.4018/978-1-61692-871-1.ch012

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Abstract

This chapter is concerned with a set of optimization problems associated to crop rotation scheduling in the context of vegetable crop production according to some ecological criteria: no crop of the same botanic family is planted in sequence, green manure and fallow periods must be present in any schedule. A core mathematical model called the crop rotation scheduling model is proposed to represent these ecological criteria together with specific technical constraints associated to the growing of vegetable crops. Three optimization problems based on crop rotation schedules are written in detail in this chapter. For each problem, the authors present a general modeling framework and a solution methodology based on a technique known as column generation, which iteratively builds crop rotation plans for a number of plots. Some extensions are also presented, with the aim of incorporating additional characteristics found in production field conditions. This chapter ends with a brief discussion on a set of computational experiments and some suggestions for future research.

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