Two models of inventory system with stochastic demand and deteriorating items: case study of a local cheese factory

Dhaiban, Ali Khaleel

doi:10.1007/s12597-021-00532-6

Cited by 4 publications

(1 citation statement)

References 29 publications

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“…The supply-chain system is a cascade system composed of multiple links, and its upstream and downstream enterprises are committed to selling products to consumers at the lowest operating costs and the fastest speed. With the trend of globalization, more and more enterprises and researchers pay attention to the management and optimization of the supply-chain system, especially from the perspective of production–storage–sales [ 1 , 2 , 3 , 4 , 5 ], the supply-chain system to optimize management. In the modern supply-chain system, the operating environment of the supply-chain system is complex, and the challenges it faces include many aspects such as natural disasters [ 6 , 7 ], public health [ 8 , 9 , 10 ], and wars [ 11 , 12 , 13 ].These will lead to changes in the market environments, causing market demand fluctuations.Especially in recent years, the emergence of crises such as coronavirus disease 2019 (COVID-19)and the Russian–Ukrainian war put the world supply-chain system in a state of extreme complexity, high uncertainty, and disruption.…”

Section: Introductionmentioning

confidence: 99%

Research on Real-Time Robust Optimization of Perishable Supply-Chain Systems Based on Digital Twins

Zhang

et al. 2023

Sensors

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Aiming at the real-time robust optimization problem of perishable supply-chain systems in complex environments, a real-time robust optimization scheme based on supply-chain digital twins is proposed. Firstly, based on the quantitative logical relationship between production and sales of single-chain series supply-chain system products, the state space equation of the supply-chain system with logical characteristics, structural characteristics, and quantitative characteristics was constructed, and twin data were introduced to construct the digital twins of supply chains based on the state-space equation. Secondly, the perishable supply-chain system in complex environments was regarded as an uncertain closed-loop system from the perspective of the state space equation, and then a robust H∞ controller design strategy was proposed, and the supply-chain digital twins was used to update and correct the relevant parameters of the supply-chain system in real-time, to implement the real-time robust optimization based on the supply-chain digital twins. Finally, the simulation experiment was carried out with a cake supply-chain production as an example. The experimental results show that the real-time updating of relevant parameters through the digital twins can help enterprise managers to formulate reasonable management plans, effectively avoid the shortage problem of enterprises in the cake supply-chain system, and reduce the maximum inventory movement standard deviation of each link by 12.65%, 6.50%, and 14.87%, and the maximum production movement standard deviation by 70.21%, 56.84%, and 45.19%.

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Section: Introductionmentioning

confidence: 99%

Research on Real-Time Robust Optimization of Perishable Supply-Chain Systems Based on Digital Twins

Zhang

et al. 2023

Sensors

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Optimization design of supply chain network based on BP neural network performance evaluation and feedback mechanism

Wu,

Liu

2024

Concurrency and Computation

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SummaryThis paper proposes a supply chain network design method suitable for multi‐product and multi‐inventory models, and uses the improved BP neural network to evaluate and provide feedback on the collaborative performance of the supply chain, adjusting the supply chain network design scheme on time. In the context of the Internet of Things (IoT) in manufacturing, it has been found that supply chain operations are difficult to meet personalized customer needs with high precision and quality. Therefore, we adopted a dynamic library strategy, supply chain network optimization model, hybrid algorithm, and the improved BP neural network to solve the above problems. First, this paper designs a corresponding inventory strategy selection mechanism for the various ordering methods of retailers in the manufacturing IoT environment. Based on this, we have constructed a dual objective model for a sustainable supply chain network to minimize total cost and maximize customer satisfaction. Second, we have developed a hybrid improved Grey Wolf and Whale Algorithm (OLDGWOA) that can accurately solve the above model. The hybrid algorithm divides the population into two parts through opposition‐based learning, and then we use the improved grey wolf algorithm and whale algorithm to solve the two populations, and seek the optimal solution in the results, resulting in a hybrid algorithm. Finally, we constructed a supply chain performance evaluation model and feedback mechanism based on the improved BP neural network to adjust inventory strategies and network design at any time. We also validated the developed model and algorithm through numerical examples, and the results showed that: (1) the hybrid algorithm has certain advantages in search and solution speed, (2) the advantages of supply chain network design based on supply chain performance evaluation and feedback mechanisms, and (3) the trade‐off between ordering methods and inventory strategies, as well as the trade‐off between location and inventory strategies.

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Multi-item stochastic inventory model for deteriorating items with power demand pattern under partial backlogging and joint replenishment

Gupta,

Mishra

2024

Ann Oper Res

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Two models of inventory system with stochastic demand and deteriorating items: case study of a local cheese factory

Cited by 4 publications

References 29 publications

Research on Real-Time Robust Optimization of Perishable Supply-Chain Systems Based on Digital Twins

Research on Real-Time Robust Optimization of Perishable Supply-Chain Systems Based on Digital Twins

Optimization design of supply chain network based on BP neural network performance evaluation and feedback mechanism

Multi-item stochastic inventory model for deteriorating items with power demand pattern under partial backlogging and joint replenishment

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