Predicting the effects of city logistics schemes
Eiichi Taniguchi,
Russell G. Thompson and
Tadashi Yamada
Transport Reviews, 2003, vol. 23, issue 4, 489-515
Abstract:
City logistics aims globally to optimize logistics systems within an urban area by considering the costs and benefits of schemes to the public and private sectors alike. Private shippers and freight operators aim to reduce their freight costs, while the community attempts to alleviate traffic congestion and environmental problems. City logistics initiatives attempt to minimize the total costs of freight movement within urban areas. Schemes for reducing the environmental and social costs as well as the economic costs are sought. This paper describes the development and application of mathematical computer-based models that have been used in the planning and evaluation of city logistics schemes. A detailed description of several modelling approaches that have been developed to predict the effects of specific city logistics schemes is presented. Integrated modelling approaches that combine both optimization and simulation, such as dynamic flow simulation and multi-agent systems, allow the effects of city logistics schemes to be predicted.
Date: 2003
References: Add references at CitEc
Citations: View citations in EconPapers (11)
Downloads: (external link)
http://hdl.handle.net/10.1080/01441640210163999 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:transr:v:23:y:2003:i:4:p:489-515
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TTRV20
DOI: 10.1080/01441640210163999
Access Statistics for this article
Transport Reviews is currently edited by Professor David Banister and Moshe Givoni
More articles in Transport Reviews from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().