Utilização de um algoritmo genético na otimização do lucro de uma propriedade agrícola

Adair Santa Catarina; Miguel Angel Uribe Opazo; Sirlei Lourdes Bach

doi:10.4025/actasciagron.v24i0.2407

Farm profit optimization using a genetic algorithm

Adair Santa Catarina UNIOESTE
Miguel Angel Uribe Opazo UNIOESTE
Sirlei Lourdes Bach UNIVEL

DOI: https://doi.org/10.4025/actasciagron.v24i0.2407

Abstract

This paper presents a Genetic Algorithm used to optimize the profit of an agricultural farm. A software prototype called “AG Optimizer” was created to apply a Genetic Algorithm in this optimization. A comparison between the optimization results using a Genetic Algorithm and deterministic method was made. The profit calculated through deterministic method, Simplex Method, was R$ 34,639.85 whereas the Genetic Algorithm provided a profit varying between R$ 32,756.91 and R$ 34,387.08. These values confirm that Genetic Algorithms can be used to optimize the profit in agricultural farms

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Author Biography

Adair Santa Catarina, UNIOESTE

Possui graduação em Engenharia Agricola pela Universidade Estadual do Oeste do Paraná (1993) , graduação em Informática pela Universidade Estadual do Oeste do Paraná (1998) e mestrado em Engenharia Agrícola pela Universidade Estadual do Oeste do Paraná (2000) . Atualmente é Professor assistente da Universidade Estadual do Oeste do Paraná. Tem experiência na área de Engenharia Agrícola , com ênfase em Máquinas e Implementos Agrícolas. Atuando principalmente nos seguintes temas: Algoritmos Genéticos, Otimização, Programação Linear, Planejamento Agrícola Currículo Lattes

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Published

2008-04-30

How to Cite

Catarina, A. S., Uribe Opazo, M. A., & Bach, S. L. (2008). Farm profit optimization using a genetic algorithm. Acta Scientiarum. Agronomy, 24, 1473-1480. https://doi.org/10.4025/actasciagron.v24i0.2407

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Issue

Vol 24 (2002)

Section

Agronomy

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I Declare that current article is original and has not been submitted for publication, in part or in whole, to any other national or international journal.

The copyrights belong exclusively to the authors. Published content is licensed under Creative Commons Attribution 4.0 (CC BY 4.0) guidelines, which allows sharing (copy and distribution of the material in any medium or format) and adaptation (remix, transform, and build upon the material) for any purpose, even commercially, under the terms of attribution.

2.0

2019CiteScore

60th percentile

2.0

2019CiteScore

60th percentile