Y. Bao, P. Llagostera Blasco, D. Babot, L. M. Plà Aragonés
Selecting the most profitable slaughterhouse, based on pig growth patterns, is crucial for max-imizing profitability. This study utilizes the K-means method to identify growth patterns and employs the Gompertz model to fit these patterns. A Mixed Integer Linear Programming (MILP)-based decision support tool(DST) is proposed, which evaluating the impact of various GPPs on slaughterhouse selection, and formulating optimal marketing strategies. This research was validated using experimental growth data from 120 pigs, categorized into three performance clusters: high, medium, and low. The results demonstrate that aligning pigs’ profitability characteristics with suitable GPPs optimized slaughter decisions and improved profits. Specifically, the three clusters achieved profit levels of 4.24 ct €/kg, 1.63 ct €/kg, and -3.13 ct €/kg, respectively. This study provides a practical DST to optimize slaughterhouse selection and marketing strategies based on growth characteristics.
Keywords: Pig growth patterns, Optimization, MILP, Slaughterhouse selection, Gompertz.
Scheduled
OR in Agriculture
June 13, 2025 9:00 AM
MR 1