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Spatially Integrated Models to Improve Urban Freight Transport Systems

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  • Full or part time
    Prof P Chhetri
  • Application Deadline
    Applications accepted all year round

About This PhD Project

Project Description

The project aims to develop a “sustainable urban freight distribution,” model which maximises the distribution
efficiency, while minimising the environmental and social impacts, of the distribution of goods in urban areas. It aims to optimise the complete door-to-door logistics chain to enhance liveability of urban areas as places to live and work.

Research Problem

Urban Freight Transport (UTF) is indispensable to the functioning of urban systems as it is required to replenish
stocks of food and other retail goods in shops, to deliver documents, parcels and other supplies to offices and to
remove household waste from urban areas. Although UFT has these important roles in the economic welfare of cities and therefore supports urban economies, it has a number of negative effects including road congestion, air quality, Greenhouse gas emissions, noise pollution and public safety. Inefficiency in freight distribution in urban areas contributes to these negative effects. The logistics inefficiency in UFT can be improve by managing low load factors and empty running, reduced number of deliveries or unconsolidated distribution, and long dwell times at loading and unloading points. Technology-driven solutions to these challenges are required to reduce this inefficiency, which leads to additional costs for transport operators or users.

Proposed Output

This project will generate innovative spatially integrated solutions to improve urban freight transport by enabling
economies of scale to be achieved through urban consolidation, to promote efficiency, and to enhance performance.

This project is aligned to the research priority of the Urban Future ECP to generate innovative spatially integrated big-data driven optimisation models/tools to “inform urban decision-making and to promote and advance the efficient design, planning and delivery of sustainable urban environments and services” using Smart Cities Analytics.

C. Proposed Postgraduate Research Programme

School: School of Business IT and Logistics
Program name: PhD (Supply Chain & Logistics)
Course code: DR202
Enabling Capability Platform (ECP) Alignment : Global Business Innovation

Related Subjects



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