A Multistage Stochastic Optimization Model for Resilient Pharmaceutical Supply Chain in COVID-19 Pandemic Based on Patient Group Priority

Опубликована: Май 3, 2024

In response to challenges brought about by the COVID-19 pandemic in pharmaceutical supply chain (PSC), this study design production-inventory-allocation problem improve resiliency of PSC during pandemics. It is essential involve prioritizing patients based on their health status, ensuring those at higher risk disease have sufficient access medication. paper, we develop a multistage stochastic mixed-integer optimization model that considers various aspects including multiproduct, multi-period, patient group prioritization, human resource capacity, and emergency safety stock which are crucial efficient functioning pandemic. We aim minimize total expected costs purchasing cost medicine from primary suppliers, inventory, hiring, transportation, backorder penalty, ordering costs. This approach demands as parameters classifies machine learning methods. The results present optimal decision for allocation, flow, resources, transportation under diverse scenarios. perform some analysis scenarios inventory decisions. show all types increase demand rises except effectively reduces shortages among vulnerable patients.

Язык: Английский

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The Confluence of AI and Big Data Analytics in Industry 4.0: Fostering Sustainable Strategic Development

Journal of the Knowledge Economy, Год журнала: 2024, Номер unknown

Опубликована: Июль 1, 2024

Язык: Английский

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Neuroevolution reinforcement learning for multi-echelon inventory optimization with delivery options and uncertain discount

Engineering Applications of Artificial Intelligence, Год журнала: 2024, Номер 134, С. 108670 - 108670

Опубликована: Май 28, 2024

Язык: Английский

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Collaborative supply chain network design under demand uncertainty: A robust optimization approach

International Journal of Production Economics, Год журнала: 2024, Номер 279, С. 109465 - 109465

Опубликована: Ноя. 12, 2024

Язык: Английский

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A modified multi-agent proximal policy optimization algorithm for multi-objective dynamic partial-re-entrant hybrid flow shop scheduling problem

Engineering Applications of Artificial Intelligence, Год журнала: 2024, Номер 140, С. 109688 - 109688

Опубликована: Ноя. 27, 2024

Язык: Английский

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