Genetic Algorithm for Constrained Optimization: A Case Study on Feed Formulation
DOI:
https://doi.org/10.32628/CSEIT25111676Keywords:
Brute force, Machine learning, Evolutionary methodsAbstract
The necessity for effective and economical feed formulation techniques has increased due to the growing demand for premium animal products worldwide. This study provides an account of the Brute Force method and the Genetic Algorithm (GA), another tremendously useful feed formulation optimization tool. experimental results show that while the GA algorithm fulfills the complexity of optimal solutions, their computation time is significantly less than that of Brute Force, thus leaving the feasibility and economy of the solution intact, especially with an increasing number of ingredients. Modern feed formulation met through up-to-date optimization methods and software in an in-depth analysis of the methods of feed formulation is what this study presents while addressing technology as a crucial instrument in solving problems associated with cost, sustained viability, and food security within the livestock industry.
📊 Article Downloads
References
D. D. Uyeh, R. Mallipeddi, T. Pamulapati, T. Park, J. Kim, S. Woo, and Y. Ha, “Title,” Comput. Electron. Agric., vol. 155, pp. 1–11, 2018. DOI: https://doi.org/10.1016/j.compag.2018.08.031
R. Eeswaran, A. P. Nejadhashemi, A. Faye, D. Min, P. V. V. Prasad, and I. A. Ciampitti, “Title,” Agronomy, vol. 12, no. 1818, 2022. DOI: https://doi.org/10.3390/agronomy12081818
E. O. Omidiora, B. O. Adegoke, and G. A. Aderounmu, “Title,” J. Biol. Agric. Healthc., vol. 3, pp. 69–76, 2013.
C. Castrodeza, P. Lara, and T. Peña, “Title,” Agric. Syst., vol. 86, pp. 76–96, 2005. DOI: https://doi.org/10.1016/j.agsy.2004.08.004
L. K. Helmuth, Minimum Cost Beef Backgrounding Ration Utilizing Alternative Feedstuffs & Stochastic Prices, M.S. thesis, North Dakota State Univ., Fargo, ND, USA, 1995.
C. Pomar and A. Remus, “Title,” J. Anim. Sci., vol. 100, no. 124, 2022. DOI: https://doi.org/10.1093/jas/skac247.237
A. V. Suresh, “Title,” in Aqua Feed Formulation, Academic Press, 2016, pp. 21–32. DOI: https://doi.org/10.1016/B978-0-12-800873-7.00002-6
P. Saxena, “Feed formulation software: A comparative study,” 2010. [Online]. Available: https://www.researchgate.net/doi:10.1079/PAVSNNR20116057. [Accessed: Oct. 19, 2024].
D. D. Uyeh, T. Pamulapati, R. Mallipeddi, T. Park, S. Asem-Hiablie, S. Woo, J. Kim, Y. Kim, and Y. Ha, “Title,” Anim. Feed Sci. Technol., vol. 256, p. 114211, 2019. DOI: https://doi.org/10.1016/j.anifeedsci.2019.114211
R. Abd Rahman, L. A. Chooi, and R. Ramli, “Title,” World Acad. Sci. Eng. Technol., vol. 70, pp. 467–475, 2010.
P. Saxena and M. Chandra, “Animal diet formulation models: A review (1950–2010),” Anim. Sci. Rev., pp. 189–197, 2011.
Association of American Feed Control Officials (AAFCO), Official Publication 2000. Atlanta, GA, USA: AAFCO, 2000.
B. Alhijawi and A. Awajan, “Genetic algorithms: Theory, genetic operators, solutions, and applications,” Evol. Intell., vol. 17, pp. 1–12, 2023, doi:10.1007/s12065-023-00822-6. DOI: https://doi.org/10.1007/s12065-023-00822-6
M. Z. Fan, A. Archbold, A. Kristensen, and B. J. McBride, “Nutrient digestibility and metabolism in ruminants,” PubMed Cent., Apr. 2020. [Online]. Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC7153313/.
FeedMU2, “FeedMU2,” 2009. [Online]. Available: http://feedmu.codeplex.com. [Accessed: Oct. 19, 2024].
Eco-Mix, “Eco-Mix,” 1998–2005. [Online]. Available: http://www.logicsoftsolutions.com. [Accessed: Oct. 19, 2024].
Dr. Kuntal, R. Gupta, and V. Patil, “Comparative study on feed formulation software: A short review,” Zenodo, 2017, doi:10.5281/zenodo.803466.
Hybrimin, “Hybrimin.” [Online]. Available: https://hybrimin.com/. [Accessed: Oct. 19, 2024].
MSD Veterinary Manual, “Nutritional requirements of dairy cattle.” [Online]. Available: https://www.msdvetmanual.com/management-and-nutrition/nutrition-dairy-cattle/nutritional-requirements-of-dairy-cattle. [Accessed: Feb. 26, 2025].
National Dairy Development Board (NDDB), Animal Nutrition Booklet. Anand, India: NDDB. [Online]. Available: https://www.nddb.coop/sites/default/files/pdfs/Animal-Nutrition-booklet.pdf. [Accessed: Feb. 26, 2025].
NutriOpt, “NutriOpt.” [Online]. Available: https://www.nutriopt.com. [Accessed: Oct. 19, 2024].
P. Saxena, “Feed formulation software: A comparative study,” 2010. [Online]. Available: https://www.researchgate.net/doi:10.1079/PAVSNNR20116057. [Accessed: Oct. 19, 2024]. DOI: https://doi.org/10.1079/PAVSNNR20116057
R. Abd Rahman, L. A. Chooi, and R. Ramli, “Investigating feed mix problem approaches: An overview and potential solution,” World Acad. Sci. Eng. Technol., vol. 70, pp. 467–475, 2010.
W. N. W. Ab. Rahman and L. M. Sie, “FeedMixer web application for animal feed formulation,” in Recent Advances on Computer Engineering, 2015, ISBN: 978-1-61804-336-8.
WinFeed 2.8, “WinFeed 2.8,” 2012. [Online]. Available: http://www.winfeed.com/download/demo.shtm. [Accessed: Oct. 19, 2024].
“Animal feed formulation software solutions,” Feed Mill of the Future. [Online]. Available: https://www.feedmillofthefuture.com/formulation-nutrition/article/15442806/animal-feed-formulation-software-solutions. [Accessed: Oct. 19, 2024].
Downloads
Published
Issue
Section
License
Copyright (c) 2025 International Journal of Scientific Research in Computer Science, Engineering and Information Technology
This work is licensed under a Creative Commons Attribution 4.0 International License.
