Urban freight demand estimation: A probability distribution based method

Abstract : The lack of data is one of the most common problems when dealing with the design of solutions that optimize urban freight transport (City Logistics Projects). In fact, to be able to process an effective City Logistics Projects for a certain area of the city, it is necessary to have the data concerning the number of daily deliveries that each commercial activity receives in this area, with detailed information regarding the time of delivery, the type of used vehicle and the amount of delivery. Only in this way is it possible to have a correct and realistic dimensioning of the freight demand. In the reality, it is not always possible to have this data for an adequate period of time. This paper, starting from the existing literature on demand forecasting and from an analysis of real data, provides the proposal of an alternative method of forecasting the demand for goods for a given area in the city when only the typology of commercial activities and a small amount of data are known.
Document type :
Conference papers
Liste complète des métadonnées

https://hal-emse.ccsd.cnrs.fr/emse-01858195
Contributor : Florent Breuil <>
Submitted on : Monday, August 20, 2018 - 11:03:13 AM
Last modification on : Tuesday, April 9, 2019 - 5:00:17 PM

Identifiers

  • HAL Id : emse-01858195, version 1

Citation

Alexandra Lagorio, Jesus Gonzalez-Feliu, Roberto Pinto. Urban freight demand estimation: A probability distribution based method. 7th International Conference on Information Systems, Logistics and Supply Chain, ILS 2018, INSA Lyon, Jul 2018, Lyon, France. pp.415-422. ⟨emse-01858195⟩

Share

Metrics

Record views

76