01554191

Component

The negative environmental impacts from urban freight transport to a large extent are derived from the fact that conventionally fuelled vehicles are mainly used for transporting goods. Many countries have implemented regulations aimed at setting high technical parameters for conventionally fuelled vehicles in order to reduce their negative impacts, however, in the long term these seem to be insufficient. This, combined with the issue of oil resources depletion, leads to the need to search for alternative forms of delivery transport. One of them is the concept of implementing cargo bicycles. However, due to its limited range and capacity it is usually impractical for bicycles to serve recipients directly and effectively from warehouses outside the city. This has an effect on the structure of the logistics networks in which the deliveries are made, leading to the establishment of intermediate nodes supplied by the main warehouse, which are then directly used by bicycles for the final stage of deliveries. This type of distribution requires the appropriate location of intermediate nodes to be determined. When it is necessary to indicate the appropriate location for more than one transit node, the optimization process becomes much more difficult, and its computational complexity rises dramatically. This paper describes the development of a genetic algorithm for optimizing the location of multiple transit nodes in logistics networks. The model was applied to design a bicycle freight transport and logistics network in the accordance with the constraints resulting from the characteristics of this kind of delivering system.

This paper was sponsored by TRB committee AT015 Freight Transportation Planning and Logistics.

01550057

15-3043

English

15p

2015

Transportation Research Board 94th Annual Meeting

Digital/other

Figures; References; Tables

Algorithms; Bicycles; Courier service; Delivery service; Freight traffic; Location; Logistics; Network nodes; Optimization; Supply chain management; Urban goods movement

Freight Transportation; Pedestrians and Bicyclists; Planning and Forecasting; Terminals and Facilities; I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2015 Paper #15-3043

TRIS, TRB, ATRI

Dec 30 2014 1:01PM