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Bazan Flores, Emory Pablo [Author]; Fe Gamarra, Candice Maria [Author]; Taquía Gutiérrez, Jose Antonio [Author]; García López, Yván Jesús [Author]; Herberger, David [Author]; Hübner, Marco [Author]

Demand Forecast Model and Route Optimization to Improve the Supply of an SME in the Bakery Sector - [published Version]

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  • Media type: E-Article; Text
  • Title: Demand Forecast Model and Route Optimization to Improve the Supply of an SME in the Bakery Sector
  • Contributor: Bazan Flores, Emory Pablo [Author]; Fe Gamarra, Candice Maria [Author]; Taquía Gutiérrez, Jose Antonio [Author]; García López, Yván Jesús [Author]; Herberger, David [Author]; Hübner, Marco [Author]
  • Published: Hannover : publish-Ing., 2023
  • Published in: Proceedings of the Conference on Production Systems and Logistics: CPSL 2023 - 2 ; https://doi.org/10.15488/15326
  • Issue: published Version
  • Language: English
  • DOI: https://doi.org/10.15488/15321; https://doi.org/10.15488/15326
  • Keywords: Konferenzschrift ; ARIMA ; Route Optimization ; Clark-Wright ; Demand Forecasting ; Supply Management Improvement
  • Origination:
  • Footnote: Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
  • Description: 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
  • Access State: Open Access