# A GENETIC ALGORITHM FOR CROP ROTATION

### Angelo Aliano Filho, Helenice de Oliveira Florentino, Margarida Vaz Pato

#### Abstract

In the last few years, crop rotation has gained attention due to its economic, environmental and social importance which explains why it can be highly beneficial for farmers. This paper presents a mathematical model for the Crop Rotation Problem (CRP) that was adapted from literature for this highly complex combinatorial problem. The CRP is devised to find a vegetable planting program that takes into account green fertilization restrictions, the set-aside period, planting restrictions for neighboring lots and for crop sequencing, demand constraints, while, at the same time, maximizing the profitability of the planted area. The main aim of this study is to develop a genetic algorithm and test it in a real context. The genetic algorithm involves a constructive heuristic to build the initial population and the operators of crossover, mutation, migration and elitism. The computational experiment was performed for a medium dimension real planting area with 16 lots, considering 29 crops of 10 different botanical families and a two-year planting rotation. Results showed that the algorithm determined feasible solutions in a reasonable computational time, thus proving its efficacy for dealing with this practical application.

#### References

- Altieri, M. A. (2002). Agroecologia: bases científicas para uma agricultura sustentável. Guaíba.
- Gliessman, S. R. (2000). Agroecologia: Processos ecológicos em agricultura sustentável. UFRGS.
- Lemalade, J. L., Nagih, A., and Plateau, G. (2011). A mip flow model for crop-rotation planning in a context of forest sustainable development. In Annals of Operations Research 190, pages 149-164.
- Santos, L. M. R. (2009). Programac¸ a˜o de rotac¸ a˜o de culturas - modelos e métodos de soluc¸ a˜o. Tese de doutorado, Universidade de Sa˜o Paulo, ICMC - Sa˜o Carlos.
- Santos, L. M. R., Michelon, P. R. H., Arenales, M. N., and Santos, R. H. S. (2011). Crop rotation scheduling with adjacency constraint. In Annals of Operations Research 190, pages 165-180.

#### Paper Citation

#### in Harvard Style

Aliano Filho A., de Oliveira Florentino H. and Vaz Pato M. (2012). **A GENETIC ALGORITHM FOR CROP ROTATION** . In *Proceedings of the 1st International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,* ISBN 978-989-8425-97-3, pages 454-457. DOI: 10.5220/0003761904540457

#### in Bibtex Style

@conference{icores12,

author={Angelo Aliano Filho and Helenice de Oliveira Florentino and Margarida Vaz Pato},

title={A GENETIC ALGORITHM FOR CROP ROTATION},

booktitle={Proceedings of the 1st International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},

year={2012},

pages={454-457},

publisher={SciTePress},

organization={INSTICC},

doi={10.5220/0003761904540457},

isbn={978-989-8425-97-3},

}

#### in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,

TI - A GENETIC ALGORITHM FOR CROP ROTATION

SN - 978-989-8425-97-3

AU - Aliano Filho A.

AU - de Oliveira Florentino H.

AU - Vaz Pato M.

PY - 2012

SP - 454

EP - 457

DO - 10.5220/0003761904540457