Scipediacontent: Scipediacontent moved page Draft content 515483473 to Abuhasel content 2026b

2026-05-21T07:47:08Z

Scipediacontent moved page Draft content 515483473 to Abuhasel content 2026b

Scipediacontent: Created page with " == Abstract ==
This study outlines a hybrid Monte Carlo Simulation-Linear Programming framework to increase the level of operational efficiency of a multistage supply cha..."

2026-05-21T07:47:05Z

Created page with " == Abstract == <p>This study outlines a hybrid Monte Carlo Simulation-Linear Programming framework to increase the level of operational efficiency of a multistage supply cha..."

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== Abstract ==

<p>This study outlines a hybrid Monte Carlo Simulation-Linear Programming framework to increase the level of operational efficiency of a multistage supply chain. This model is an integration of probabilistic simulation and deterministic optimization to take into account the effects of demand variability, lead-time variability, and capacity variability on profitability and the overall service delivery performance. The suggested framework is tested with the help of a multi-product, multi-stage supply chain case study that is implemented on the basis of a publicly available dataset containing around 9000 transactional records. Monte Carlo simulation generates random uncertainty scenarios, whereas linear programming finds the ideal decisions related to production, distribution, and inventory levels for each iteration. The results suggest that reducing the amount of demand variability and better capacity planning resulted in a good performance with an expected profit of $328,100.16, a profit variance of 3.72× 109, and a service level of 94.3%. The result of the sensitivity analysis shows that demand variability and lead times have a negative effect on profit, while optimal capacity planning enhances operational flexibility. The MCS-LP provides an advantage to the use of stochastic and deterministic methods for risk-aware decision making and has the potential to be computationally scalable and efficient for uncertaintydriven supply chain design. The general approach provides a decisionsupport tool for managers considering how to balance costs, risk, service quality, and uncertainty in ever-changing industrial contexts.OPEN ACCESS Received: 14/11/2025 Accepted: 13/01/2026 Published: 20/03/2026</p>

== Document ==
<pdf>Media:Draft_content_515483473-3576-document.pdf</pdf>

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Abuhasel content 2026b - Revision history

Scipediacontent: Scipediacontent moved page Draft content 515483473 to Abuhasel content 2026b

Scipediacontent: Created page with " == Abstract == This study outlines a hybrid Monte Carlo Simulation-Linear Programming framework to increase the level of operational efficiency of a multistage supply cha..."

Scipediacontent: Created page with " == Abstract ==
This study outlines a hybrid Monte Carlo Simulation-Linear Programming framework to increase the level of operational efficiency of a multistage supply cha..."