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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
Copyright: © 2011 |Pages: 32
ISBN13: 9781609604721|ISBN10: 1609604725|EISBN13: 9781609604738
DOI: 10.4018/978-1-60960-472-1.ch204
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MLA

dos Santos, Lana, et al. "A Linear Optimization Approach for Increasing Sustainability in Vegetable Crop Production." Green Technologies: Concepts, Methodologies, Tools and Applications, edited by Information Resources Management Association, IGI Global, 2011, pp. 236-267. https://doi.org/10.4018/978-1-60960-472-1.ch204

APA

dos Santos, L., Arenales, M., Costa, A., & Santos, R. (2011). A Linear Optimization Approach for Increasing Sustainability in Vegetable Crop Production. In I. Management Association (Ed.), Green Technologies: Concepts, Methodologies, Tools and Applications (pp. 236-267). IGI Global. https://doi.org/10.4018/978-1-60960-472-1.ch204

Chicago

dos Santos, Lana, et al. "A Linear Optimization Approach for Increasing Sustainability in Vegetable Crop Production." In Green Technologies: Concepts, Methodologies, Tools and Applications, edited by Information Resources Management Association, 236-267. Hershey, PA: IGI Global, 2011. https://doi.org/10.4018/978-1-60960-472-1.ch204

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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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