Selection of slaughterhouse to deliver fattened pigs depending on growth curves
Year: 2025
Type: article
Abstract: Context: Modern fattening farms require effective interdisciplinary decision-making tools to ensure profitability. Objective: This paper introduces a mixed integer linear programming (MILP) - based decision tool, to optimize the transportation strategy selecting the most profitable slaughterhouse and exploring the impact of key factors such as pig prices, feed costs, and mortality rates. Methods: The proposed tool is based on a mixed integer linear programming (MILP) model, the pig growth modeling by Gompertz model and the payment grid of different slaughterhouses. Results and conclusions: Our findings confirm the selection of the most suitable slaughterhouse significantly enhances the economic outcome, and that the current increment in slaughter weight to about 120 kg leads to a larger fattening period. Piglet mortality did not affect the optimal delivery plan but: for every 1% increase in mortality rate, there was a loss of 0.9 ct €/kg. In addition, four growth curves fit from experimental data are used to compare their optimal marketing strategies. The base case scenario outperformed the official profits reported to the sector by 12.49 ct €/kg liveweight. Pigs with low growth generated losses of -0.42 ct €/kg while medium growth pigs with 4.24 ct €/kg outperformed higher growth pigs (1.29 ct €/kg). The feeding cost advantage makes medium-growth pigs more profitable. The optimal fattening period was 22 weeks except for medium growth pigs (which was from 20 to 21 weeks). Significance: With the rise of digital farms and precision livestock farming , Decision Support Systems (DSS) based on accurate growth curves plays a key role in slaughterhouse selection and developing effective marketing strategy, outperforming industry averages.
Source: Agricultural Systems
Language: English
Subfield: Agronomy and Crop Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: hybrid
Estimated APC paid: $4,000
OpenAlex ID: W4411436849
