Economic and ecological optimization of the London urban logistics system considering infection risk during pandemic periods

Urban delivery, especially the last-mile delivery, has become an increasingly important area in the global supply chain along with the boom of e-commerce. Delivery companies and merchants can introduce some innovative solutions such as the equipment of autonomous vehicles (AVs) to decrease their ope...

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Main Author: Xuan Feng
Format: Article
Language:English
Published: Kharazmi University 2021-05-01
Series:International Journal of Supply and Operations Management
Subjects:
Online Access:http://www.ijsom.com/article_2839_c93659748150b7cfd9b8df5f61958426.pdf
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spelling doaj-34aca962c88f4f8ebf24f008c23919002021-09-29T04:40:43ZengKharazmi UniversityInternational Journal of Supply and Operations Management2383-13592383-25252021-05-018211413310.22034/ijsom.2021.2.22839Economic and ecological optimization of the London urban logistics system considering infection risk during pandemic periodsXuan Feng0School of Strategy and Leadership, Coventry University, Coventry, UKUrban delivery, especially the last-mile delivery, has become an increasingly important area in the global supply chain along with the boom of e-commerce. Delivery companies and merchants can introduce some innovative solutions such as the equipment of autonomous vehicles (AVs) to decrease their operating costs, environmental impact, and social risks during the delivery process. This paper mainly develops a mathematical model to get the best allocation of AVs among city logistics centers (CLCs) as a mixed delivery method. The advantage of the presented model stems from considering the equipment cost, the delivery cost, and the CO2 emission, which is measured through social carbon cost (SCC). In addition, this paper establishes a risk model considering the impact of seasonal variations to evaluate the infection risk of delivery during pandemic periods for four potential delivery scenarios: customers going to CLCs, ordering online and picking-up at CLCs, delivering by traditional vehicles (TVs), and delivering by the mixed method with the optimal allocation of AVs. The research finds the optimal allocation for a London case, reveals the relationship between the nominal service capacity (NCpa) of CLCs and the optimal number of CLCs equipped with AVs, concludes that the more CLCs are equipped with AVs, the fewer CO2 emissions and the fewer citizens will be infected, and provides some managerial insights that may help delivery companies and merchants make appropriate decisions about the allocation of AVs.http://www.ijsom.com/article_2839_c93659748150b7cfd9b8df5f61958426.pdfurban logisticscost optimizationco2 emissioninfection risknet present value,supply chain management
collection DOAJ
language English
format Article
sources DOAJ
author Xuan Feng
spellingShingle Xuan Feng
Economic and ecological optimization of the London urban logistics system considering infection risk during pandemic periods
International Journal of Supply and Operations Management
urban logistics
cost optimization
co2 emission
infection risk
net present value,supply chain management
author_facet Xuan Feng
author_sort Xuan Feng
title Economic and ecological optimization of the London urban logistics system considering infection risk during pandemic periods
title_short Economic and ecological optimization of the London urban logistics system considering infection risk during pandemic periods
title_full Economic and ecological optimization of the London urban logistics system considering infection risk during pandemic periods
title_fullStr Economic and ecological optimization of the London urban logistics system considering infection risk during pandemic periods
title_full_unstemmed Economic and ecological optimization of the London urban logistics system considering infection risk during pandemic periods
title_sort economic and ecological optimization of the london urban logistics system considering infection risk during pandemic periods
publisher Kharazmi University
series International Journal of Supply and Operations Management
issn 2383-1359
2383-2525
publishDate 2021-05-01
description Urban delivery, especially the last-mile delivery, has become an increasingly important area in the global supply chain along with the boom of e-commerce. Delivery companies and merchants can introduce some innovative solutions such as the equipment of autonomous vehicles (AVs) to decrease their operating costs, environmental impact, and social risks during the delivery process. This paper mainly develops a mathematical model to get the best allocation of AVs among city logistics centers (CLCs) as a mixed delivery method. The advantage of the presented model stems from considering the equipment cost, the delivery cost, and the CO2 emission, which is measured through social carbon cost (SCC). In addition, this paper establishes a risk model considering the impact of seasonal variations to evaluate the infection risk of delivery during pandemic periods for four potential delivery scenarios: customers going to CLCs, ordering online and picking-up at CLCs, delivering by traditional vehicles (TVs), and delivering by the mixed method with the optimal allocation of AVs. The research finds the optimal allocation for a London case, reveals the relationship between the nominal service capacity (NCpa) of CLCs and the optimal number of CLCs equipped with AVs, concludes that the more CLCs are equipped with AVs, the fewer CO2 emissions and the fewer citizens will be infected, and provides some managerial insights that may help delivery companies and merchants make appropriate decisions about the allocation of AVs.
topic urban logistics
cost optimization
co2 emission
infection risk
net present value,supply chain management
url http://www.ijsom.com/article_2839_c93659748150b7cfd9b8df5f61958426.pdf
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