Spare parts supply chain network modeling based on a novel scale-free network and replenishment path optimization with Q learning

Wang, Fang; Lin, Lin

doi:10.1016/j.cie.2021.107312

Cited by 9 publications

(2 citation statements)

References 24 publications

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“…In this paper, the main body of the supply chain network is abstracted into nodes, and the directed edges in the network represent the trust relationship between nodes. The evolution of supply chain network conforms to the growth and preferential connection features of the scale-free network [11]. The modeling of supply chain network needs to solve three problems:…”

Section: Improved Trust Modelmentioning

confidence: 99%

Optimization of the Trust Propagation on Supply Chain Network Based on Blockchain Plus

Chen¹,

Shan²

2022

JIMD

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The decentralization of blockchain technology greatly improves the trust relationship in the supply chain network. In view of the lack of trust, uncertainty, and asymmetry in the supply chain network, this paper integrates the blockchain technology to build a network dynamics model of trust representation, calculation, and propagation, and explores how the blockchain influences the supply chain network. The result indicates that the network scale increased by 115.89%, the network connectivity increased by 60.31%, and the average shortest path decreased by 4.95%, after the blockchain trust framework had been deployed in the agricultural supply chain. Meanwhile, the network topology performance such as degree distribution and average clustering coefficient were optimized to varying degrees. Taking agricultural supply chain as an example, the practical significance of topological change was explained. Overall, the blockchain trust mechanism improves the topology of the supply chain network by affecting the trust relationship between nodes.

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Section: Improved Trust Modelmentioning

confidence: 99%

Optimization of the Trust Propagation on Supply Chain Network Based on Blockchain Plus

Chen¹,

Shan²

2022

JIMD

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“…With the object of better preserving vegetable commodities, the relevant research is mainly divided into technical and metrological types.The first is technical research, Cao Tingting et al adopted light technology to maintain the quality of fruits and vegetables [2].The second type is a metrological study,Cao Yu et al studied the problem of multi-product joint replenishment by establishing the average replenishment cost model [3].Kiil K et al positively investigated the impact of automatic replenishment and expanded the current understanding of automatic replenishment programs [4]. Wang and Lin proposed a model based on a new scale-free network for the purpose of optimizing the supply chain network replenishment path and analyzing the network static and dynamic performance of [5]. Sharma S et al fully characterized the optimal replenishment strategy of the dual-product system and provided a method to calculate the optimal replenishment volume so that they further developed a heuristic multi-product system [6].…”

Section: Introductionmentioning

confidence: 99%

Research on supermarket replenishment volume prediction based on LSTM and PSO algorithm

Yan,

Deng

2024

EHSS

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In order to meet people's health needs and reduce economic losses, the new fresh suppliers carried out real, reliable and targeted market demand analysis so that they formulate automatic pricing and replenishment decision of vegetable commodities with the aim of providing fresh and nutritious vegetable commodities. This paper adopts the apriori model to explore the correlation between vegetables and reflects the relationship between total sales and cost plus pricing by the linear fitting method.This paper further uses the LSTM time series prediction model, time sliding sequence and PSO particle swarm algorithm to predict the various vegetable categories of daily supplement and pricing in the next week, so as to maximize the business super profit. The results showed that the price of each vegetable category had a significant negative correlation with the sales volume and the dynamic prediction of replenishment quantity and pricing data had obvious application effect, which effectively helped the supermarket to make pricing and replenishment decisions.

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Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective

Xu,

Elomri,

Baldacci

et al. 2024

Ann Oper Res

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Industrial 4.0 (I4.0) is believed to revolutionize supply chain (SC) management and the articles in this domain have experienced remarkable increments in recent years. However, the existing insights are scattered over different sub-topics and most of the existing review papers have ignored the underground decision-making process using OR methods. This paper aims to depict the current state of the art of the articles on SC optimization in I4.0 and identify the frontiers and limitations as well as the promising research avenue in this arena. In this study, the systematic literature review methodology combined with the content analysis is adopted to survey the literature between 2013 and 2022. It contributes to the literature by identifying the four OR innovations to typify the recent advances in SC optimization: new modeling conditions, new inputs, new decisions, and new algorithms. Furthermore, we recommend four promising research avenues in this interplay: (1) incorporating new decisions relevant to data-enabled SC decisions, (2) developing data-enabled modeling approaches, (3) preprocessing parameters, and (4) developing data-enabled algorithms. Scholars can take this investigation as a means to ignite collaborative research that tackles the emerging problems in business, whereas practitioners can glean a better understanding of how to employ their OR experts to support digital SC decision-making.

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Spare parts supply chain network modeling based on a novel scale-free network and replenishment path optimization with Q learning

Cited by 9 publications

References 24 publications

Optimization of the Trust Propagation on Supply Chain Network Based on Blockchain Plus

Optimization of the Trust Propagation on Supply Chain Network Based on Blockchain Plus

Research on supermarket replenishment volume prediction based on LSTM and PSO algorithm

Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective

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