Optimal Crops Selection using Multiobjective Evolutionary Algorithms

Authors

  • Ricardo Brunelli National University of Asuncion
  • Christian von Lücken National University of Asuncion

DOI:

https://doi.org/10.1609/aimag.v30i2.2212

Keywords:

multiobjective optimization, crops selection, evolutionary algorithms

Abstract

Farm managers have to deal with many conflicting objectives when planning which crop to cultivate. Soil characteristics are extremely important when determining yield potential. Fertilization and liming are commonly used to adapt soils to the nutritional requirements of the crops to be cultivated. Planting the crop that will best fit the soil characteristics is an interesting alternative to minimize the need for soil treatment, reducing costs and potential environmental damages. In addition, farmers usually look for investments that offer the greatest potential earnings with the least possible risks. According to the objectives to be considered the crop selection problem may be difficult to solve using traditional tools. Therefore, this work proposes an approach based on Multiobjective Evolutionary Algorithms to help in the selection of an appropriate cultivation plan considering five crop alternatives and five objectives simultaneously.

Author Biographies

Ricardo Brunelli, National University of Asuncion

Ricardo Brunelli works as research assistant and auxiliary professor at the Polytechnic Faculty of the National University of Asunción. He received a degree in Computer Engineering from the same University. His research interest focuses on the application of bio-inspired computation and multiobjective optimization, in areas related to agricultural activity, environmental preservation and safe production.

Christian von Lücken, National University of Asuncion

Christian von Lücken is a full time research professor at the Polytechnic Faculty of the National University of Asunción. He received a degree in Computer Engineering from the Catholic University of Asunción and a Master of Science degree in Computer Science from the University of Asunción. Current subject of his work is the hybridization of metaheuristics with more classical artificial intelligence and operations research methods.

 

 

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Published

2009-06-20

How to Cite

Brunelli, R., & von Lücken, C. (2009). Optimal Crops Selection using Multiobjective Evolutionary Algorithms. AI Magazine, 30(2), 96. https://doi.org/10.1609/aimag.v30i2.2212

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Section

Articles