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Research on Optimization of Supermarket Chain Distribution Routes Under O2O Model

Dealing with the store distribution problems in transformation and upgrading of supermarket chains under Online-to-Offline (O2O) e-commerce model and considering the factors that affect the distribution cost and customer satisfaction, such as distribution distance, number of distribution vehicles, a...

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Autor principal: He, Dan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9001826/
http://dx.doi.org/10.1007/s41660-022-00246-2
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author He, Dan
author_facet He, Dan
author_sort He, Dan
collection PubMed
description Dealing with the store distribution problems in transformation and upgrading of supermarket chains under Online-to-Offline (O2O) e-commerce model and considering the factors that affect the distribution cost and customer satisfaction, such as distribution distance, number of distribution vehicles, and delivery time, an O2O store distribution optimization model has been constructed with the purpose of minimizing total distribution cost. Moreover, a two-stage heuristic algorithm for ordering nearest distribution and mileage saving planning has been designed. The applicability and effectiveness of the model and method have been verified by enterprise case data collected. The results have shown that the total cost of distribution is obviously reduced compared with the accounting results of related models, which is suitable for supermarket chains or single-store retail enterprises with low probability of order splitting and distribution due to the shortage of certain products.
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spelling pubmed-90018262022-04-12 Research on Optimization of Supermarket Chain Distribution Routes Under O2O Model He, Dan Process Integr Optim Sustain Short Technical Note Dealing with the store distribution problems in transformation and upgrading of supermarket chains under Online-to-Offline (O2O) e-commerce model and considering the factors that affect the distribution cost and customer satisfaction, such as distribution distance, number of distribution vehicles, and delivery time, an O2O store distribution optimization model has been constructed with the purpose of minimizing total distribution cost. Moreover, a two-stage heuristic algorithm for ordering nearest distribution and mileage saving planning has been designed. The applicability and effectiveness of the model and method have been verified by enterprise case data collected. The results have shown that the total cost of distribution is obviously reduced compared with the accounting results of related models, which is suitable for supermarket chains or single-store retail enterprises with low probability of order splitting and distribution due to the shortage of certain products. Springer Nature Singapore 2022-04-12 2022 /pmc/articles/PMC9001826/ http://dx.doi.org/10.1007/s41660-022-00246-2 Text en © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Short Technical Note
He, Dan
Research on Optimization of Supermarket Chain Distribution Routes Under O2O Model
title Research on Optimization of Supermarket Chain Distribution Routes Under O2O Model
title_full Research on Optimization of Supermarket Chain Distribution Routes Under O2O Model
title_fullStr Research on Optimization of Supermarket Chain Distribution Routes Under O2O Model
title_full_unstemmed Research on Optimization of Supermarket Chain Distribution Routes Under O2O Model
title_short Research on Optimization of Supermarket Chain Distribution Routes Under O2O Model
title_sort research on optimization of supermarket chain distribution routes under o2o model
topic Short Technical Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9001826/
http://dx.doi.org/10.1007/s41660-022-00246-2
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