Distributionsledelse og logistikledelse
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Urban Freight Analytics
Big Data, Models, and Artificial Intelligence
Udgivet af Taylor & Francis Ltd
ISBN
9781032199368
Om denne bog
Urban Freight Analytics examines the key concepts associated with the development and application of decision support tools for evaluating and implementing city logistics solutions. New analytical methods are required for effectively planning and operating emerging technologies including the Internet of Things (IoT), I…
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Bogdetaljer
Forfatter
Ali G. Qureshi, Eiichi Taniguchi, Russell G. Thompson
Forlag
Taylor & Francis Ltd
Kategori
Distributionsledelse og logistikledelse
ISBN-13
9781032199368
EAN
9781032199368
Format
Indbundet
Sprog
Engelsk
sider
170
Undertitel
- Big Data, Models, and Artificial Intelligence
Produktbeskrivelse
Urban Freight Analytics examines the key concepts associated with the development and application of decision support tools for evaluating and implementing city logistics solutions. New analytical methods are required for effectively planning and operating emerging technologies including the Internet of Things (IoT), Information and Communication Technologies (ICT), and Intelligent Transport Systems (ITS).The book provides a comprehensive study of modelling and evaluation approaches to urban freight transport. It includes case studies from Japan, the US, Europe, and Australia that illustrate the experiences of cities that have already implemented city logistics, including analytical methods that address the complex issues associated with adopting advanced technologies such as autonomous vehicles and drones in urban freight transport.Also considered are future directions in urban freight analytics, including hyperconnected city logistics based on the Physical Internet (PI), digital twins, gamification, and emerging technologies such as connected and autonomous vehicles in urban areas. An integrated modelling platform is described that considers multiple stakeholders or agents, including emerging organisations such as PI companies and entities such as crowd-shippers as well as traditional stakeholders such as shippers, receivers, carriers, administrators, and residents.This bookPresents procedures for evaluating city logistics technologies and policy measuresProvides an overview of advanced modelling approaches, including agent-based model and machine learningHighlights the essential features of optimisation and simulation models applied to city logisticsDiscusses how models incorporating more uncertainty and dynamic data can be used to improve the sustainability and resilience of urban freight systemsThe book is ideal for graduate students in civil and environmental engineering and logistics management, urban planners, transport engineers, and logistics specialists.
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