Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/325759 
Year of Publication: 
2023
Citation: 
[Journal:] Operations Research Perspectives [ISSN:] 2214-7160 [Volume:] 10 [Article No.:] 100273 [Year:] 2023 [Pages:] 1-13
Publisher: 
Elsevier, Amsterdam
Abstract: 
Broiler chickens are specially raised for meat production and their supply chain is composed of breeders, hatcheries, feed mills, farms, slaughterhouses, wholesalers, and retailers. The coordination between supply chain players has great potential to streamline production and increase competitiveness in the market. A critical element in the decision-making process of this agri-system is the weight gain of broiler chickens. Variability in chicken growth patterns can affect production plans in practice. The most efficient weight estimation models require sensors in real-time, which are not available in many companies. Thus, some small farms require a simpler approach to adjust production planning based on the uncertainty of chickens' weight while they transition to new technologies. This research proposes an optimization-based methodology for the integration of farms and slaughterhouses to plan production under chicken growth uncertainty. The methodology includes two models: (i) a two-stage stochastic model that supports lot-sizing and inventory management decisions while considering scenarios of chicken growth uncertainty; and (ii) a mixed-integer linear programming model that supports lot allocation. We present the results of implementing the methodology in a poultry company in Santa Marta (Colombia), where we improved costs by 8.6% while meeting tactical, biological, and biosecurity constraints.
Subjects: 
Growth uncertainty
Lot sizing decisions
Poultry supply chain
Two-stage stochastic programming
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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