Abstract
Vehicle Routing problems are highly complex problems for which different Artificial Intelligence techniques have been used. In this paper, we propose two agent-oriented self-organization models for the dynamic version of the problem with time windows. The first model relies on a spatial representation, and the second is based on a space-time representation of the agents' action zones, which are able to maintain a good distribution of the vehicles on the environment. This distribution provides better results than traditional methods by allowing the agents to take their decisions while anticipating future changes in the system's parameters. © 2010 Springer-Verlag.
Cite
CITATION STYLE
Zeddini, B., & Zargayouna, M. (2010). Multidimentional self-organization for online time-constrained vehicle routing problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6071 LNAI, pp. 170–179). https://doi.org/10.1007/978-3-642-13541-5_18
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