Master production scheduling of a pet food plant using a rolling horizon optimization methodology
This work addresses the Master Production Scheduling problem (MPS) of a pet food manufacturing plant. The production process comprises several stages, starting with the dosing of raw materials and ending with the packaging and storage of the final product. The plant has a fixed number of production...
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| Formato: | Articulo |
| Lenguaje: | Español |
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2023
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| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/157011 |
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I19-R120-10915-1570112023-08-29T20:03:54Z http://sedici.unlp.edu.ar/handle/10915/157011 Master production scheduling of a pet food plant using a rolling horizon optimization methodology Programación maestra de la producción de una planta de alimentos para mascotas mediante una metodología de optimización basada en horizonte rodante Cusimano, Joan Ríos, Romina A. Herrero, Fernando Faba, Emilce Marchetti, Pablo A. 2023-05 2023-08-29T15:47:12Z es Ciencias Informáticas Master production scheduling Optimization Rolling Horizon Algorithm Pet Food Manufacturing Programación maestra de la producción Optimización Horizonte rodante Fabricación de alimento para mascotas This work addresses the Master Production Scheduling problem (MPS) of a pet food manufacturing plant. The production process comprises several stages, starting with the dosing of raw materials and ending with the packaging and storage of the final product. The plant has a fixed number of production lines, being the critical equipment the extruders and packaging machines available. Given a medium-term horizon (3 to 5 months) disaggregated into weeks, for each line the production volumes per product, which are associated to different families, must be defined. A mixed-integer linear mathematical model (MILP), considering the main constraints of the problem, combined with a Rolling Horizon algorithm to solve the complete horizon has been developed. The proposed methodology has been applied to the MPS problem of a large-scale industrial facility that produces hundreds of products and families. Based on the problem’s dimensions, a parameter analysis of the algorithm has been performed to find the best balance between time and solution quality. As a result, by applying the proposed methodology considerable improvements were obtained regarding key indicators such as minimum batch size per family, compliance with the stock policy, and solution times compared with the current method. Este trabajo aborda la Programación Maestra de la Producción (PMP) de una planta de elaboración de alimentos para mascotas. El proceso de fabricación consiste en varias etapas, comenzando con la dosificación de las materias primas y finalizando con el envasado y almacenamiento del producto final. La planta cuenta con un número fijo de líneas de producción, siendo el equipamiento crítico las extrusoras y envasadoras disponibles. Dado un horizonte de mediano plazo (3 a 5 meses) desagregado en semanas, para cada línea se desea definir los volúmenes de producción por producto, los cuales se encuentran asociados a diferentes familias. Se desarrolló un modelo matemático mixto-entero lineal (MILP), considerando las principales restricciones del problema, combinado con un algoritmo de Horizonte Rodante para la resolución del horizonte completo. La metodología propuesta fue aplicada al problema de PMP de una instalación industrial de gran escala, que elabora cientos de productos y familias. En base a las dimensiones del problema, se realizó un análisis de parámetros del algoritmo para encontrar el mejor balance entre tiempo y calidad de la solución. Como resultado, al aplicar la metodología propuesta se obtuvieron mejoras considerables en cuanto a indicadores clave como lote mínimo por familia, cumplimiento de la política de stock y tiempos de resolución en comparación con el método vigente. Sociedad Argentina de Informática e Investigación Operativa Articulo Articulo http://creativecommons.org/licenses/by-nc/4.0/ Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) application/pdf 186-205 |
| institution |
Universidad Nacional de La Plata |
| institution_str |
I-19 |
| repository_str |
R-120 |
| collection |
SEDICI (UNLP) |
| language |
Español |
| topic |
Ciencias Informáticas Master production scheduling Optimization Rolling Horizon Algorithm Pet Food Manufacturing Programación maestra de la producción Optimización Horizonte rodante Fabricación de alimento para mascotas |
| spellingShingle |
Ciencias Informáticas Master production scheduling Optimization Rolling Horizon Algorithm Pet Food Manufacturing Programación maestra de la producción Optimización Horizonte rodante Fabricación de alimento para mascotas Cusimano, Joan Ríos, Romina A. Herrero, Fernando Faba, Emilce Marchetti, Pablo A. Master production scheduling of a pet food plant using a rolling horizon optimization methodology |
| topic_facet |
Ciencias Informáticas Master production scheduling Optimization Rolling Horizon Algorithm Pet Food Manufacturing Programación maestra de la producción Optimización Horizonte rodante Fabricación de alimento para mascotas |
| description |
This work addresses the Master Production Scheduling problem (MPS) of a pet food manufacturing plant. The production process comprises several stages, starting with the dosing of raw materials and ending with the packaging and storage of the final product. The plant has a fixed number of production lines, being the critical equipment the extruders and packaging machines available. Given a medium-term horizon (3 to 5 months) disaggregated into weeks, for each line the production volumes per product, which are associated to different families, must be defined. A mixed-integer linear mathematical model (MILP), considering the main constraints of the problem, combined with a Rolling Horizon algorithm to solve the complete horizon has been developed.
The proposed methodology has been applied to the MPS problem of a large-scale industrial facility that produces hundreds of products and families. Based on the problem’s dimensions, a parameter analysis of the algorithm has been performed to find the best balance between time and solution quality. As a result, by applying the proposed methodology considerable improvements were obtained regarding key indicators such as minimum batch size per family, compliance with the stock policy, and solution times compared with the current method. |
| format |
Articulo Articulo |
| author |
Cusimano, Joan Ríos, Romina A. Herrero, Fernando Faba, Emilce Marchetti, Pablo A. |
| author_facet |
Cusimano, Joan Ríos, Romina A. Herrero, Fernando Faba, Emilce Marchetti, Pablo A. |
| author_sort |
Cusimano, Joan |
| title |
Master production scheduling of a pet food plant using a rolling horizon optimization
methodology |
| title_short |
Master production scheduling of a pet food plant using a rolling horizon optimization
methodology |
| title_full |
Master production scheduling of a pet food plant using a rolling horizon optimization
methodology |
| title_fullStr |
Master production scheduling of a pet food plant using a rolling horizon optimization
methodology |
| title_full_unstemmed |
Master production scheduling of a pet food plant using a rolling horizon optimization
methodology |
| title_sort |
master production scheduling of a pet food plant using a rolling horizon optimization
methodology |
| publishDate |
2023 |
| url |
http://sedici.unlp.edu.ar/handle/10915/157011 |
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