Modeling tactical planning decisions through a linear optimization model in sow farms

This paper deals with tactical planning decisions for breeding farms producing piglets through a linear optimization model. A medium-term planning horizon based on weekly periods is considered. The proposed model maximizes the profit of the farm and takes into account sow herd dynamics, housing faci...

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Detalles Bibliográficos
Autores: Rodríguez Sánchez, Sara Verónica, Pla Aragonés, Lluís Miquel, Albornoz Sanhueza, Victor Manuel
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2012
País:España
Institución:Universitat de Lleida (UdL)
Repositorio:Repositori Obert UdL
OAI Identifier:oai:repositori.udl.cat:10459.1/57098
Acceso en línea:https://doi.org/10.1016/j.livsci.2011.09.006
http://hdl.handle.net/10459.1/57098
Access Level:acceso abierto
Palabra clave:Tactical decisions
Planning
Sow herd management
Descripción
Sumario:This paper deals with tactical planning decisions for breeding farms producing piglets through a linear optimization model. A medium-term planning horizon based on weekly periods is considered. The proposed model maximizes the profit of the farm and takes into account sow herd dynamics, housing facilities, reproduction management, available stocks and a target quota of a weekly number of farrowing to integrate piglet production into the pig supply chain management. As result, an optimal replacement policy of sows and a scheduling of purchases of gilts during the whole planning horizon are provided. The model is solved using the algebraic modeling language ILOG OPL 6.1 with CPLEX 11.2 as the linear optimization solver. The article also discusses results obtained from a sensitivity analysis performed to assess the suitability of the model approach and the benefits of representing real variability over time against time homogeneity. In addition, the analysis and results presented lead to better understand sow herd dynamics over a finite time-horizon and corresponding performance.