Optimal distribution and waste management of Covid-19 vaccines from vaccination centers’ satisfaction perspective – A fuzzy time window-based VRP

Transportation Research Part E Logistics and Transportation Review, Год журнала: 2024, Номер 183, С. 103454 - 103454

Опубликована: Фев. 10, 2024

Язык: Английский

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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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A review of decision support systems in the internet of things and supply chain and logistics using web content mining

Supply Chain Analytics, Год журнала: 2024, Номер 6, С. 100063 - 100063

Опубликована: Март 19, 2024

The Internet of Things (IoT) has attracted the attention researchers and practitioners in supply chains logistics (LSCs). IoT improves monitoring, controlling, optimizing, planning LSCs. Several have reviewed IoT-based LSCs publications indexed by academic journals focusing on decision-making. Decision support systems (DSS) are infancy stage This paper reviews IoT-LSCs from DSS perspective. We propose a new framework for helping decision-makers implement based decisions that need to be made describing transition scheme simple, if-then analytical decision-making approaches IoT-LSCs. Adopter II is an extension framework, which layer called 'decision' been added enable implementing improve list predefined processes Although literature review analysis provides valuable insights, wide range related information available online. study also utilizes web content mining approach first time analyze context. results show IoT-LSC field involves two emerging themes, blockchain chain 5.0, mainstream i.e., big data analytics management.

Язык: Английский

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A machine learning model with linear and quadratic regression for designing pharmaceutical supply chains with soft time windows and perishable products

Decision Analytics Journal, Год журнала: 2023, Номер 9, С. 100325 - 100325

Опубликована: Сен. 15, 2023

Product perishability is an important problem in Pharmaceutical Supply Chains (PSC). Demand and unpredictability add enormous complexity to successfully implementing efficient Chain Network Design (PSCND). This study develops a mathematical model for the PSCND. The two objective functions used minimize total cost delivery penalty due schedule violations involving Soft Time Windows (STWs). Using STW strategy Distribution Center (DC) allocation empowers decision-makers include time-based performance metric DC evaluation based on degree of urgency or need part. Moreover, Linear Regression (LR) Quadratic (QR) Machine Learning (ML) algorithms are proposed forecast demand decrease possibility shortage We show that QR has better than LR In approach, medicine forecasted by technique. Goal Attainment (GA) method solve suggested model. Finally, sensitivity analysis managerial perspectives offered. numerical outcomes leads PSC, reducing cost, decreasing shortage, increasing customer satisfaction with consideration.

Язык: Английский

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Radiation-Immune Spintronic Binary Synapse and Neuron for Process-in-Memory Architecture

IEEE Magnetics Letters, Год журнала: 2024, Номер 15, С. 1 - 5

Опубликована: Янв. 1, 2024

This paper proposes an SEU-hardened task-scheduling logic in memory XNOR/XOR neuron and synapse circuits. Using C-element magnetic tunnel junction enhances immunity against single event upset injection to the design. Also, using architecture eliminates need access external decreases power delay. Furthermore, carbon nanotube field-effect transistor leads lower leakage static current caused by higher gate control these transistors. Compared state-of-the-art counterparts, proposed design offers at least 31%, 17%, 3% improvement regarding power, delay product, area product

Язык: Английский

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Multi-Retention STT-MRAM Architectures for IoT: Evaluating the Impact of Retention Levels and Memory Mapping Schemes

IEEE Access, Год журнала: 2024, Номер 12, С. 26562 - 26580

Опубликована: Янв. 1, 2024

In recent years, the energy consumption of IoT edge nodes has significantly increased due to communication process. This necessitates need offload more computation minimize data transmission over network. To achieve this, higher-performance CPUs and memory are required on nodes. this context, we propose an energy-efficient architecture specifically designed for STT-MRAM is a promising technology that offers potential replacements SRAM Flash in devices. exhibits notable advantages traditional technologies, such as non-volatility retention without continuous power supply efficiency, resulting extended battery life portable devices applications. Its higher density scalability through standard fabrication processes further enhances its appeal next-generation solutions. However, high write main disadvantage. Previous works have explored relaxation CPU cache but there extend approach paper, multi-retention memory. Additionally, mapping scheme suggested examine impact relaxed levels consumption. best our knowledge, first study thoroughly investigate optimal thermal stability factor value applications while also considering mapping. The proposed reduces by average 70% up 83% compared currently used non-volatile architecture. Furthermore, two mappings easy use savings just 5% away from ideal

Язык: Английский

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Cold chain optimisation models: A systematic literature review

Computers & Industrial Engineering, Год журнала: 2025, Номер unknown, С. 110972 - 110972

Опубликована: Фев. 1, 2025

Язык: Английский

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A Revision of Production Planning and Scheduling Methods in Pharmaceutical Industry

Lecture notes in networks and systems, Год журнала: 2025, Номер unknown, С. 49 - 58

Опубликована: Янв. 1, 2025

Язык: Английский

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A Multi-product Humanitarian Supply Chain Network Design Problem: A Fuzzy Multi-objective and Robust Optimization Approach

International journal of engineering. Transactions B: Applications, Год журнала: 2024, Номер 37(5), С. 941 - 958

Опубликована: Янв. 1, 2024

In today's dynamic and unpredictable world, the planning management of humanitarian supply chains hold paramount importance. Efficient logistics is crucial for effectively delivering essential aid resources to affected areas during disasters emergencies, ensuring timely support relief vulnerable populations. this research, we addressed a novel chain network design problem that considers product differentiation demand uncertainty. Specifically, simultaneously incorporate non-perishable, perishable, blood products as critical components network. The formulated multi-objective mixed-integer linear programming model aiming minimize total cost traveled distance by making location, allocation, production decisions. To enhance realism, account uncertainty in areas. tackle challenging problem, proposed two-phase solution methodology. Firstly, employed robust optimization approach establish deterministic counterpart stochastic model. Subsequently, an efficient fuzzy programming-based reformulates into single-objective form, accommodating decision-makers' preferences. Numerical instances are solved investigate performance methodologies. results demonstrate effectiveness our finding non-dominated solutions, enabling decision-makers explore trade-offs. Also, sensitivity analyses were conducted provide more insights. Finally, some suggestions presented extend current work feature researchers.

Язык: Английский

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A review on unsupervised learning algorithms and applications in supply chain management

International Journal of Production Research, Год журнала: 2024, Номер unknown, С. 1 - 51

Опубликована: Авг. 19, 2024

Due to pressing challenges such as high market volatility, complex global logistics, geopolitical turmoil and environmental sustainability, compounded by radical events the COVID-19 pandemic, complexity of supply chain management has reached unprecedented levels. Together with increasing data availability computing power, machine learning algorithms can help address these challenges. In particular, unsupervised be invaluable in extracting new knowledge from unstructured, unlabelled data. This article systematically reviews current state research on techniques management. We propose a classification framework that categorises literature sample based drivers, sectors, sources, UL algorithms, reveal following insights. The most common applications are information processing typical operations optimisation problems location planning vehicle routing. From an algorithmic perspective, clustering other traditional dominate recent approaches, owing their popularity simplicity, robustness accessibility. More advanced generative have been slow gain acceptance. contrast paradigms, mainly plays supporting role. large number publications using real-world confirms importance maturity

Язык: Английский

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