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Optimizing the Profit of an Agricultural Company through the Application of Genetic Algorithms

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Rodes Angelo B. Da Silva, Héliton Pandorfi, Gledson Luiz P. De Almeida, Nicole Viana Da Silva

Rodes Angelo Da B Silva, Héliton Pandorfi, Gledson Luiz De P Almeida and Nicole Viana Da Silva. Optimizing the Profit of an Agricultural Company through the Application of Genetic Algorithms. International Journal of Computer Applications 183(24):39-42, September 2021. BibTeX

	author = {Rodes Angelo B. Da Silva and Héliton Pandorfi and Gledson Luiz P. De Almeida and Nicole Viana Da Silva},
	title = {Optimizing the Profit of an Agricultural Company through the Application of Genetic Algorithms},
	journal = {International Journal of Computer Applications},
	issue_date = {September 2021},
	volume = {183},
	number = {24},
	month = {Sep},
	year = {2021},
	issn = {0975-8887},
	pages = {39-42},
	numpages = {4},
	url = {},
	doi = {10.5120/ijca2021921613},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


For the proper planning of production processes in agricultural companies, resources are needed that allow the development of methodologies capable of bringing optimal solutions that support decision making. The aim of this study was develop a prototype to optimize the profit of an agricultural company through the application of genetic algorithms. Obtaining data regarding production processes belong to a dairy company specialized in the manufacture of dairy products, located in the municipality of Caruaru, state of Pernambuco. An on-site visit was carried out to survey the entire production process of the products under study; interview with the business owner to learn about their main market interests; collection of data for the elaboration of a business model, with emphasis on product diversification and improvement in the company's profit margin. From the data, an “AG planning” prototype was developed using the python language and the tkinter library. For the implementation, the objective based function was first developed. in profits and 10 restrictions were modeled based on manufacturing time of each product, number of employees and hours worked. Three repetitions of 3, 6 and 10 executions of the algorithm were performed to verify the highest possible profit value. The most significant increase in the profit margin was identified infirst simulation with 3 runs. With the using genetic algorithms it was possible to plan the weekly production of the company.


  1. Cormem,T.H., Leiserson, C.E., Rivest, R.L. and Stein, C. 2002. Algorithms: theory and practice (2. ed.). Rio de Janeiro.
  2. Embrapa. 2020..Applications of Infrared Thermography (TIV) in beef cattle. Available at: Accessed on 12/24/2020.
  3. Goldbarg, M.C. and Pacca, H.L.L. 2000. Combinatorial Optimization and Linear Programming: Models and Algorithms. Rio de Janeiro: Editora Campus.
  4. Holland, J.H 1975.Adaptation in natural and artificial systems. Ann Arbor: University of Michigan Press.
  5. Linden, R. 2008. Genetic algorithms: an important tool of computational intelligence. 2nd ed. RiverinJanuary: EditoraBrasportLivros e Multimídia Ltda.
  6. Martin, N.B. Costs: agricultural production cost system. Inf. Economic., São Paulo, vol. 24, no. 9, p. 97-122, 1994
  7. Moreira, D.A. Administration of production and operations. São Paulo: Cengage Learning, 2008.
  8. Oliveira, A.J .An intelligent decision support system for planning rural businesses. 1995. Dissertation (Masters) - Federal University of Viçosa, Viçosa, 1995.
  9. Ribeiro, R. And Fortes, B. 2015.Linear programming: A contribution to the management of a rural property. XXXV National Meeting of Production Engineering (ENEGEP), Fortaleza-CE
  10. Rodrigues, W.O.P., Reis Neto, J. F. and Souza, C.C. 2012. Genetic Algorithms as a Decision Support Tool in Dairy Production Planning. Capital Scientific Magazine – Electronic (RCCe),10.
  11. Salokhe, V.M. and Pariyar, M.P. 1990. Optimum farm planning by linear programming for Tarai belt of Nepal. Agricultural Mechanization in Asia, Afrik and Latin America, Tokyo, 21(4):76-81.
  12. Santa Catarina, A.,Opazo, B.A.D. and Bach, S.L.2002.Use of a genetic algorithm to optimize the profit of an agricultural property, Acta ScientiarumMaringá, . 24(5): 1473-1480,
  13. Stacanelli, T.M., Moura, R.A.,Silva, Y.V.B.,Silva, G., Da Silva, A.M. 2015. Application of linear programming to optimize production in a dairy located in the mid-west region of minas gerais. XXXV National Meeting of Production Engineering.
  14. Viana, G.V.R. 1998. Metaheuristics and scheduleparallel in combinatorial optimization. Fortaleza: EUFC.


Animal production, optimization, artificial intelligence