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Modeling and Analyzing the Inventory Level for Demand Uncertainty in the VUCA World: Evidence From Biomedical Manufacturer
16 references·1 citing·48 second hop
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References

  • 2000Designing and Managing the Supply Chain Concepts, Strategies, and Case Studies1,298 cited
  • 2016Introduction to Time Series and Forecasting1,190 cited
  • 2019A supervised machine learning approach to data-driven simulation of resilient supplier selection in digital manufacturing530 cited
  • 2011Simulation Modeling and Analysis with ARENA355 cited
  • 2019Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data342 cited
  • 2020Deep learning with long short-term memory networks and random forests for demand forecasting in multi-channel retail206 cited
  • 2017Variable Selection in Time Series Forecasting Using Random Forests203 cited
  • 2015On the risk-averse optimization of service level in a supply chain under disruption risks125 cited
  • 2010Evaluation of forecasting error measurements and techniques for intermittent demand100 cited
  • 2017Simulation-based single vs. dual sourcing analysis in the supply chain with consideration of capacity disruptions, big data and demand patterns90 cited
  • 2014Simulation-based optimization framework for multi-echelon inventory systems under uncertainty81 cited
  • 2007Multi-echelon inventory management in supply chains with uncertain demand and lead times: Literature review from an operational research perspective73 cited
  • 2022Predictive and prescriptive performance of bike-sharing demand forecasts for inventory management

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65 cited
  • 2004Strategic Positioning of Inventory to Match Demand in a Capital Projects Supply Chain59 cited
  • 2015Equivalence Between Out-of-Sample Forecast Comparisons and Wald Statistics49 cited
  • 2012Lean manufacturing practices in textile industries - a case study46 cited
  • Cited by

    • 2024Application of simulation and machine learning in supply chain management: A synthesis of the literature using the Sim-ML literature classification framework37 cited