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A Genetic Algorithm for Site-Specific Management Zone Delineation

Author

Listed:
  • Francisco Huguet

    (Department de Matemàtica, Universitat de Lleida, c/ Jaume II, 73, 25003 Lleida, Spain
    Department of Electronics and Informatics, Universidad Centroamericana UCA, Bulevar Los Próceres, Antiguo Cuscatlán, La Libertad 01-168, El Salvador)

  • Lluís M. Plà-Aragonés

    (Department de Matemàtica, Universitat de Lleida, c/ Jaume II, 73, 25003 Lleida, Spain
    Agrotecnio Center, Universitat de Lleida, 25198 Lleida, Spain)

  • Víctor M. Albornoz

    (Departamento de Industrias, Campus Santiago Vitacura, Universidad Técnica Federico Santa María, Av. Santa María 6400, Santiago 7650568, Chile)

  • Mauricio Pohl

    (Department of Electronics and Informatics, Universidad Centroamericana UCA, Bulevar Los Próceres, Antiguo Cuscatlán, La Libertad 01-168, El Salvador)

Abstract

This paper presents a genetic algorithm-based methodology to address the Site-Specific Management Zone (SSMZ) delineation problem. A SSMZ is a subregion of a field that is homogeneous with respect to a soil or crop property, enabling farmers to apply customized management strategies for optimizing resource use. The algorithm generates optimized field partitions using rectangular zones, applicable to both regular and irregularly shaped fields. To the best of our knowledge, the Genetic Algorithm for Zone Delineation (GAZD) is the first approach to handle the rectangular SSMZ delineation problem in irregular-shaped lands without introducing non-real data. The algorithm’s performance is compared with an exact solution based on integer linear programming. Experimental tests conducted on real-field and generated irregular-shaped instances show that while the GAZD requires longer execution times than the exact approach, it proves to be functional and robust in solving the SSMZ problem. Furthermore, the GAZD offers a set of “good enough” solutions that can be evaluated for feasibility and practical convenience, making it a valuable tool for decision-making processes. Moreover, strategies such as implementation in a compiled language and parallel processing can be used to improve the execution time performance of the algorithm.

Suggested Citation

  • Francisco Huguet & Lluís M. Plà-Aragonés & Víctor M. Albornoz & Mauricio Pohl, 2025. "A Genetic Algorithm for Site-Specific Management Zone Delineation," Mathematics, MDPI, vol. 13(7), pages 1-18, March.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:7:p:1064-:d:1620093
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    References listed on IDEAS

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    1. Víctor M. Albornoz & Marcelo I. Véliz & Rodrigo Ortega & Virna Ortíz-Araya, 2020. "Integrated versus hierarchical approach for zone delineation and crop planning under uncertainty," Annals of Operations Research, Springer, vol. 286(1), pages 617-634, March.
    2. Víctor M. Albornoz & Gabriel E. Zamora, 2021. "Decomposition-based heuristic for the zoning and crop planning problem with adjacency constraints," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 248-265, April.
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