Computer Science – Artificial Intelligence
Scientific paper
2008-09-03
Computer Science
Artificial Intelligence
Proceedings of the 7th EU/ME Workshop: Adaptive, Self-Adaptive, and Multi-Level Metaheuristics, Malaga, Spain, November 16-17,
Scientific paper
The article presents a framework for the resolution of rich vehicle routing problems which are difficult to address with standard optimization techniques. We use local search on the basis on variable neighborhood search for the construction of the solutions, but embed the techniques in a flexible framework that allows the consideration of complex side constraints of the problem such as time windows, multiple depots, heterogeneous fleets, and, in particular, multiple optimization criteria. In order to identify a compromise alternative that meets the requirements of the decision maker, an interactive procedure is integrated in the resolution of the problem, allowing the modification of the preference information articulated by the decision maker. The framework is prototypically implemented in a computer system. First results of test runs on multiple depot vehicle routing problems with time windows are reported.
Geiger Martin Josef
Wenger Wolf
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