Optimal inventory control policies of a two-stage push–pull production inventory system with lost sales under stochastic production, transportation, and external demand

Varlas, George; Vidalis, Michael; Koukoumialos, Stelios; Diamantidis, Alexandros

doi:10.1007/s11750-021-00595-0

Cited by 2 publications

(1 citation statement)

References 30 publications

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“…Varlas et al [1] explored optimal inventory management strategies by comprehensively considering stochastic production, transportation, external demand, and sales loss. They introduced an analytical model based on Markov processes.…”

Section: Introductionmentioning

confidence: 99%

Raw Material Inventory Optimization for Steel Enterprises Under Price Uncertainty

Chu,

Wu,

Cheng

2024

Proceedings of the 5th International Conference on Economic Management and Model Engineering, ICEMME 2023, November 17–19, 2023

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Due to the uncertainty of raw material prices, procurement and inventory costs account for a large proportion and are difficult to control in steel production. Aiming at the problem of raw material purchase and inventory in iron and steel enterprises with uncertain purchase price, in order to overcome the uncertainty of price and the conservatism of the solution, this paper establishes a robust optimization model for minimizing the total cost of purchase and inventory. Due to its inherent computational complexity, we introduced disturbance variables and employed duality theory to derive a tractable robust counterpart model. Finally, the model was applied to a real steel manufacturing enterprise to validate its effectiveness. The results indicate that, while the total cost of the robust model is slightly higher than that of the deterministic model for planning horizon of 3, 6, and 9, it becomes lower when the planning horizon is set to 12. For longer planning horizons, the robust model has a good effect on inventory and robustness under the condition of price fluctuations. Furthermore, we conducted an analysis of the impact of critical parameter thresholds on the total cost. The findings revealed that as the threshold value increases, the total cost also increases. Therefore, companies can select an appropriate threshold based on their specific circumstances to control costs.

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Section: Introductionmentioning

confidence: 99%

Raw Material Inventory Optimization for Steel Enterprises Under Price Uncertainty

Chu,

Wu,

Cheng

2024

Proceedings of the 5th International Conference on Economic Management and Model Engineering, ICEMME 2023, November 17–19, 2023

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Push/Pull Parts Production Policy Optimization in the ATO Environment

et al. 2021

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Within the Assembly to Order (ATO) production strategy, the common approach is to produce the parts to assemble with a Push-Make to Stock policy.In recent decades, the effects of the modern Just in Time (JIT) moved to a Pull-Make to Order policy. Assembled parts characterized by wide variety and huge storage space utilization are critical, and a proper Push/Pull production policy definition is required. An appropriate balance of storage space utilization and setup times leads to the optimization of the production policy. The aim of this paper is to define a bi-objective mathematical optimization model to assign the most suitable production policy to the parts within the production mix in an ATO industrial context. A numerical simulation and an operative case study showcases the model application, proving the industrial relevance of this research.

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Optimal inventory control policies of a two-stage push–pull production inventory system with lost sales under stochastic production, transportation, and external demand

Cited by 2 publications

References 30 publications

Raw Material Inventory Optimization for Steel Enterprises Under Price Uncertainty

Raw Material Inventory Optimization for Steel Enterprises Under Price Uncertainty

Push/Pull Parts Production Policy Optimization in the ATO Environment

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