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Demand Forecast Model and Route Optimization to Improve the Supply of an SME in the Bakery Sector

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Fecha
2023
Autor(es)
Bazán Flores, Emory Paulo
Gamarra Villanueva, Candice María Fe
Taquía Gutiérrez, José Antonio
García López, Yván Jesús
Metadatos
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Resumen
This research employs the Lean Six Sigma DMAIC methodology to address enhancing product distribution efficiency in a bakery chain. Following the diagnostic phase, demand forecasting models were developed using ARIMA and Holt Winter methods, with ARIMA demonstrating higher prediction accuracy. Furthermore, route mapping was conducted using the Clark-Wright algorithm. Key performance indicators (KPIs) such as delivery time, distance traveled, and MAPE (Mean Absolute Percentage Error) will be established for process control. Implementing these improvements aims to achieve more efficient product distribution management within the bakery chain. © 2023, Publish-Ing in cooperation with TIB - Leibniz Information Centre for Science and Technology University Library. All rights reserved.
URI
https://hdl.handle.net/20.500.12724/21363
DOI
https://doi.org/10.15488/15321
Cómo citar
Bazán, E. P., Gamarra, C. M. F., Taquía, J. A., & García, Y. J. (2023). Demand Forecast Model and Route Optimization to Improve the Supply of an SME in the Bakery Sector. . https://doi.org/10.15488/15321
Editor
Publish-Ing in cooperation with TIB - Leibniz Information Centre for Science and Technology University Library
Temas
Pendiente
ISSN
2701-6277
Evento
Proceedings of the Conference on Production Systems and Logistics
Coleccion(es)
  • Ingeniería Industrial [182]


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