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Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing

The cross-border e-commerce supply chain network (CBESCN) has extensive geographical coverage, trade barriers and complexity of cross-border logistics issues, which makes its construction and development face many challenges. This article focuses on solving the operation optimisation problem of CBES...

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Detalles Bibliográficos
Autores principales: Dong, Qingxia, Chen, Nana, Wang, Shuai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280632/
https://www.ncbi.nlm.nih.gov/pubmed/37346574
http://dx.doi.org/10.7717/peerj-cs.1407
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author Dong, Qingxia
Chen, Nana
Wang, Shuai
author_facet Dong, Qingxia
Chen, Nana
Wang, Shuai
author_sort Dong, Qingxia
collection PubMed
description The cross-border e-commerce supply chain network (CBESCN) has extensive geographical coverage, trade barriers and complexity of cross-border logistics issues, which makes its construction and development face many challenges. This article focuses on solving the operation optimisation problem of CBESCN under the background of the Internet of Things. A genetic algorithm constructed and solved the resource scheduling model of the supply chain of e-commerce enterprises in international trade. In addition, the mobile edge computing (MEC) optimisation scheme based on partial computation unloading is involved. The initial offload ratio is set and supply chain resources are allocated, then the remaining computing resources are distributed according to the server’s computing power. Finally, the offload is optimised according to the resource allocation. The experimental results show that time delay and cost adjustment strategies can improve the CBE supply chain’s comprehensive ability. The supply chain optimisation scheme proposed in this article can effectively use supply chain resources according to the requirements of computing tasks to reduce the total delay of task execution and the consumption of node computing.
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spelling pubmed-102806322023-06-21 Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing Dong, Qingxia Chen, Nana Wang, Shuai PeerJ Comput Sci Algorithms and Analysis of Algorithms The cross-border e-commerce supply chain network (CBESCN) has extensive geographical coverage, trade barriers and complexity of cross-border logistics issues, which makes its construction and development face many challenges. This article focuses on solving the operation optimisation problem of CBESCN under the background of the Internet of Things. A genetic algorithm constructed and solved the resource scheduling model of the supply chain of e-commerce enterprises in international trade. In addition, the mobile edge computing (MEC) optimisation scheme based on partial computation unloading is involved. The initial offload ratio is set and supply chain resources are allocated, then the remaining computing resources are distributed according to the server’s computing power. Finally, the offload is optimised according to the resource allocation. The experimental results show that time delay and cost adjustment strategies can improve the CBE supply chain’s comprehensive ability. The supply chain optimisation scheme proposed in this article can effectively use supply chain resources according to the requirements of computing tasks to reduce the total delay of task execution and the consumption of node computing. PeerJ Inc. 2023-06-06 /pmc/articles/PMC10280632/ /pubmed/37346574 http://dx.doi.org/10.7717/peerj-cs.1407 Text en ©2023 Dong et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.
spellingShingle Algorithms and Analysis of Algorithms
Dong, Qingxia
Chen, Nana
Wang, Shuai
Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing
title Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing
title_full Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing
title_fullStr Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing
title_full_unstemmed Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing
title_short Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing
title_sort supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing
topic Algorithms and Analysis of Algorithms
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280632/
https://www.ncbi.nlm.nih.gov/pubmed/37346574
http://dx.doi.org/10.7717/peerj-cs.1407
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