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Year 2025, Volume: 6 Issue: 2, 161 - 178, 30.12.2025
https://doi.org/10.46592/turkager.1761884

Abstract

References

  • Adjimoti GO (2018). Analysis of cropland allocation in rural areas Benin: A fractional multinomial approach. Cogent Food and Agriculture, 4(1), 1-13. https://doi.org/10.1080/23311932.2018.1488339
  • Baki SM and Cheng JK (2021). A linear programming model for product mix profit maximization in a small medium enterprise company. International Journal of Industrial Management, 9(1): 64-73.
  • Bender DA, Kline DE and McCarl BA (2023). Postoptimal linear programming analysis of farm machinery. Transactions of the American Society of Agricultural Engineers, 33(1): 15-20.
  • Bhatia M and Rana A (2020). A integrated farm model for optimal allocation of resources- a linear programming approach. Applications and Applied Mathematics: An International Journal, 15(2):1336-1347.
  • Britos B, Hernandez MA, Robles M and Trupkin DR (2022). Land market distortions and aggregate agricultural productivity : Evidence. Journal of Development Economics, 155(6): 102787. http://doi:10.1016/j.jjdeveco.2021.102787
  • Chapoto A (2013). Agricultural commercialization, land expansion, and homegrown large-scale farmers ınsights from Ghana. August.
  • Dawid I and Mohammed F (2021). The status , challenges , and prospects of agricultural production and productivity in Ethiopia: A review. International Journal of Research in Agronomy, 4(2): 108-114.
  • Goemans M (2015). Linear programming lecture notes. Linear Programming Lecture Notes, 2: 1-33.
  • Hillier FS (2008). Linear Programming: Foundations and extensions. Third Edition. Springer.
  • Igwe K, Nwaru J, Igwe C and Asumugha G (2015). Optimizing crop land allocation for smallholder farmers in central Uganda Msc thesis report. Wageningenur for Quality of Life, 15(5):1-71.
  • Khafizov R, Khafizov C, Nurmiev A and Galiev I (2018). Optimization of main parameters of tractor and unit for seeding cereal crops with regards to their impact on crop productivity. Engineering for Rural Development, 17: 168-175. https://doi.org/10.22616/ERDev2018.17.N192
  • Kunwar R and Sapkota HP (2022). An introduction to linear programming problems with some real-life applications. European Journal of Mathematics and Statistics, 3(2): 21-27. https://doi.org/10.24018/ejmath.2022.3.2.108
  • Mellaku MT, Reynolds TW and Woldeamanuel T (2018). Linear programming-based cropland allocation to enhance performance of smallholder crop production : A Pilot Study in Abaro Kebele, Ethiopia. Resources, 7(4): 76. https://doi.org/10.3390/resources7040076
  • Moulogianni C (2022). Comparison of Selected Mathematical Programming Models Used for Sustainable Land and Farm Management. Land, 11(8). https://doi.org/10.3390/land11081293
  • Munetsi GM (2023). Using operations research analytic techniques to solve the land allocation , transportation problem and decision analysis to small-scale farming : Case two farms in norton and joetech. The Degree Of Bsc Honours In Applied Mathematics With Economics, University Of Zimbabwe Faculty Of Science Mathematics And Computational Sciences
  • Patel N, Thaker M and Chaudhari C (2017). Agricultural land allocation to the major crops through linear programming model. International Journal of Science and Research (IJSR), 6(4): 2015-2018.
  • Salo A, Andelmin J and Oliveira F (2022). Decision programming for mixed-integer multi-stage optimization under uncertainty. European Journal of Operational Research, 299(2): 550-565. https://doi.org/10.1016/j.ejor.2021.12.013
  • Saxena H and Sharma S (2025). Linear programming for resource allocation and profit maximization in furniture production. Asian Journal of Pure and Applied Mathematics, 7(1), 139-147.
  • Schulze MA (2000). Linear programming for optimization. Perceptive Scientific Instruments, Inc, 0( January), 1-8. http://www.markschulze.net/LinearProgramming.pdf
  • Solaja, Abraham O, Abolaji, Abiodun J, Abioro, Adekunle M, Ekpudu, Ehimen J, Olasubulumi, Moses O (2020). Application of linear programming in production planning. Munich Personal RePEc Archive, 98226.
  • Ummah MS (2019). Managing cover crops profitably. Sustainable Agriculture Research and Education (SARE), Handbook Series Book 9, Third Edition, Maryland.
  • Worqlul AW, Jeong J, Dile YT, Osorio J, Schmitter P, Gerik T, Srinivasan R and Clark N (2017). Assessing potential land suitable for surface irrigation using groundwater in Ethiopia. Applied Geography, 85: 1-13. https://doi.org/10.1016/j.apgeog.2017.05.010
  • Zhou X, Sharma A and Mohindru V (2021). Research on linear programming algorithm for mathematical model of agricultural machinery allocation. International Journal of Agricultural and Environmental Information Systems, 12(3): 1-12. https://doi.org/10.4018/IJAEIS.2021070101

Optimization of Crop Land Allocation under Large Scale Mechanized Farm Using Linear Programming: The Case of Lole State Farm

Year 2025, Volume: 6 Issue: 2, 161 - 178, 30.12.2025
https://doi.org/10.46592/turkager.1761884

Abstract

Agriculture sector plays a crucial role in the Ethiopian economy, providing income, employment, and revenue generating, but the production and productivity are poor. Hence, resource optimization is essential for increasing efficiency and productivity. Good farm management is not only about increasing the amount of farm inputs; it also needs enhanced resource inputs managements. This study was conducted at Lole State Farm of Ethiopia which was faced by manual cropland allocation that wasn’t optimized relative to the degree of the crops' profitability. The study aimed to optimize cropland allocation through a linear objective function and constraints. The objective functions designed for Lole State Farm was to maximize crop profit per hectare by optimizing crop land allocation through satisfying various farm constraints. The parameters of the objective function were crop profit (Ethiopia Birr per hectare). In line with this, the constraints that were considered during the optimization of cropland allocation were total production costs (fertilizers, herbicides, chemicals such as pesticides, fungicides, insecticides, etc., seed, labor, and machine hour cost, crop rotation, and total land area). By subjecting the objective function to farm constraints and using linear programming, optimization of land use was achieved via mathematical modeling of linear programming. The result of the optimization indicated that wheat and potato are the first and second profitable crops, respectively, for Lole State Farm, followed by fava bean, food barley, and rapeseed as economic options and suitable for this optimization. In conclusion, the LP model optimization process has improved decision-making on cropland allocation by taking into account farm constraints.

Ethical Statement

This article does not require any Ethical Committee Decision.

References

  • Adjimoti GO (2018). Analysis of cropland allocation in rural areas Benin: A fractional multinomial approach. Cogent Food and Agriculture, 4(1), 1-13. https://doi.org/10.1080/23311932.2018.1488339
  • Baki SM and Cheng JK (2021). A linear programming model for product mix profit maximization in a small medium enterprise company. International Journal of Industrial Management, 9(1): 64-73.
  • Bender DA, Kline DE and McCarl BA (2023). Postoptimal linear programming analysis of farm machinery. Transactions of the American Society of Agricultural Engineers, 33(1): 15-20.
  • Bhatia M and Rana A (2020). A integrated farm model for optimal allocation of resources- a linear programming approach. Applications and Applied Mathematics: An International Journal, 15(2):1336-1347.
  • Britos B, Hernandez MA, Robles M and Trupkin DR (2022). Land market distortions and aggregate agricultural productivity : Evidence. Journal of Development Economics, 155(6): 102787. http://doi:10.1016/j.jjdeveco.2021.102787
  • Chapoto A (2013). Agricultural commercialization, land expansion, and homegrown large-scale farmers ınsights from Ghana. August.
  • Dawid I and Mohammed F (2021). The status , challenges , and prospects of agricultural production and productivity in Ethiopia: A review. International Journal of Research in Agronomy, 4(2): 108-114.
  • Goemans M (2015). Linear programming lecture notes. Linear Programming Lecture Notes, 2: 1-33.
  • Hillier FS (2008). Linear Programming: Foundations and extensions. Third Edition. Springer.
  • Igwe K, Nwaru J, Igwe C and Asumugha G (2015). Optimizing crop land allocation for smallholder farmers in central Uganda Msc thesis report. Wageningenur for Quality of Life, 15(5):1-71.
  • Khafizov R, Khafizov C, Nurmiev A and Galiev I (2018). Optimization of main parameters of tractor and unit for seeding cereal crops with regards to their impact on crop productivity. Engineering for Rural Development, 17: 168-175. https://doi.org/10.22616/ERDev2018.17.N192
  • Kunwar R and Sapkota HP (2022). An introduction to linear programming problems with some real-life applications. European Journal of Mathematics and Statistics, 3(2): 21-27. https://doi.org/10.24018/ejmath.2022.3.2.108
  • Mellaku MT, Reynolds TW and Woldeamanuel T (2018). Linear programming-based cropland allocation to enhance performance of smallholder crop production : A Pilot Study in Abaro Kebele, Ethiopia. Resources, 7(4): 76. https://doi.org/10.3390/resources7040076
  • Moulogianni C (2022). Comparison of Selected Mathematical Programming Models Used for Sustainable Land and Farm Management. Land, 11(8). https://doi.org/10.3390/land11081293
  • Munetsi GM (2023). Using operations research analytic techniques to solve the land allocation , transportation problem and decision analysis to small-scale farming : Case two farms in norton and joetech. The Degree Of Bsc Honours In Applied Mathematics With Economics, University Of Zimbabwe Faculty Of Science Mathematics And Computational Sciences
  • Patel N, Thaker M and Chaudhari C (2017). Agricultural land allocation to the major crops through linear programming model. International Journal of Science and Research (IJSR), 6(4): 2015-2018.
  • Salo A, Andelmin J and Oliveira F (2022). Decision programming for mixed-integer multi-stage optimization under uncertainty. European Journal of Operational Research, 299(2): 550-565. https://doi.org/10.1016/j.ejor.2021.12.013
  • Saxena H and Sharma S (2025). Linear programming for resource allocation and profit maximization in furniture production. Asian Journal of Pure and Applied Mathematics, 7(1), 139-147.
  • Schulze MA (2000). Linear programming for optimization. Perceptive Scientific Instruments, Inc, 0( January), 1-8. http://www.markschulze.net/LinearProgramming.pdf
  • Solaja, Abraham O, Abolaji, Abiodun J, Abioro, Adekunle M, Ekpudu, Ehimen J, Olasubulumi, Moses O (2020). Application of linear programming in production planning. Munich Personal RePEc Archive, 98226.
  • Ummah MS (2019). Managing cover crops profitably. Sustainable Agriculture Research and Education (SARE), Handbook Series Book 9, Third Edition, Maryland.
  • Worqlul AW, Jeong J, Dile YT, Osorio J, Schmitter P, Gerik T, Srinivasan R and Clark N (2017). Assessing potential land suitable for surface irrigation using groundwater in Ethiopia. Applied Geography, 85: 1-13. https://doi.org/10.1016/j.apgeog.2017.05.010
  • Zhou X, Sharma A and Mohindru V (2021). Research on linear programming algorithm for mathematical model of agricultural machinery allocation. International Journal of Agricultural and Environmental Information Systems, 12(3): 1-12. https://doi.org/10.4018/IJAEIS.2021070101
There are 23 citations in total.

Details

Primary Language English
Subjects Precision Agriculture Technologies
Journal Section Research Article
Authors

Bilisuma Edea 0009-0006-0851-5158

Girma Moges Ketsela 0000-0003-3611-3616

Habtamu Alemayehu 0000-0002-2751-4824

Submission Date August 10, 2025
Acceptance Date December 15, 2025
Publication Date December 30, 2025
Published in Issue Year 2025 Volume: 6 Issue: 2

Cite

APA Edea, B., Ketsela, G. M., & Alemayehu, H. (2025). Optimization of Crop Land Allocation under Large Scale Mechanized Farm Using Linear Programming: The Case of Lole State Farm. Turkish Journal of Agricultural Engineering Research, 6(2), 161-178. https://doi.org/10.46592/turkager.1761884

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