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Solving a Many-Objective Crop Rotation Problem with Evolutionary Algorithms

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Intelligent Decision Technologies

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 238))

Abstract

Crop rotation consists of alternating the types of plants grown in the same place in a planned sequence to obtain improved profits and accomplish environmental outcomes. Determining optimal crop rotations is a relevant decision-making problem in agricultural farms. This work presents a seven objective crop rotation problem considering economic, social, and environmental factors and its solution using evolutionary algorithms; to this aim, an initialization procedure and genetic operators are proposed. Five multi- and many-objective evolutionary algorithms were implemented for a given problem instance, and their results were compared. The comparison shows the methods to be used as a tool for improving decision-making in crop rotations. Also, among the compared algorithms, the RVEA obtains the best values for evaluated metrics for the studied instance.

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Acknowledgement

This work was partially supported by CONACYT Project PINV18-949

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Authors and Affiliations

  1. Universidad Nacional de Asunción, San Lorenzo, Paraguay

    Christian von Lücken, Angel Acosta & Norma Rojas

Authors
  1. Christian von Lücken
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  2. Angel Acosta
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  3. Norma Rojas
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Corresponding author

Correspondence to Christian von Lücken .

Editor information

Editors and Affiliations

  1. Gdynia Maritime University, Gdynia, Poland

    Ireneusz Czarnowski

  2. Bournemouth University, Poole, UK

    Robert J. Howlett

  3. KES International, Shoreham-by-Sea, UK

    Lakhmi C. Jain

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von Lücken, C., Acosta, A., Rojas, N. (2021). Solving a Many-Objective Crop Rotation Problem with Evolutionary Algorithms. In: Czarnowski, I., Howlett, R.J., Jain, L.C. (eds) Intelligent Decision Technologies. Smart Innovation, Systems and Technologies, vol 238. Springer, Singapore. https://doi.org/10.1007/978-981-16-2765-1_5

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