id: 06104501
dt: a
an: 06104501
au: Zargayouna, Mahdi; Zeddini, Besma
ti: Fleet organization models for online vehicle routing problems.
so: Nguyen, Ngoc Thanh (ed.), Transactions on Computational Collective
    Intelligence VII. Berlin: Springer (ISBN 978-3-642-32065-1/pbk).
    Lecture Notes in Computer Science 7270. Journal Subline, 82-102 (2012).
py: 2012
pu: Berlin: Springer
la: EN
cc: 
ut: Vehicle Routing Problems; Multiagent Systems; Organization Models
ci: 
li: doi:10.1007/978-3-642-32066-8_4
ab: Summary: Online vehicle routing problems with time windows are highly
    complex problems for which different artificial intelligence techniques
    have been used. In these problems, the exclusive optimization of the
    conventional criteria (number of vehicles and total traveled distance)
    leads to the appearance of geographic areas and/or time periods that
    are not covered by any vehicle because of their low population density.
    The transportation demands in these zones either cannot be satisfied or
    need to mobilize new vehicles. We propose two agent-oriented models
    that propose a particular dynamic organization of the vehicles, with
    the objective to minimize the appearance of such areas. The first model
    relies on a spatial representation of the agents’ action zones, and
    the second model is grounded on the space-time representation of these
    zones. These representations are capable of maintaining an equilibrated
    distribution of the vehicles on the transportation network. In this
    paper, we experimentally show that these two means of distributing
    vehicles over the network provide better results than traditional
    insertion heuristics. They allow the agents to take their decisions
    while anticipating future changes in the environment.
rv: