Genetic Algorithm for Constrained Optimization: A Case Study on Feed Formulation - Afaq Alam Khan,; Aatifa Jan, (International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025)
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.
Keywords: Brute force; Machine learning; Evolutionary methods