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 implemented in a computer system. Results of test runs on multiple depot multi-objective vehicle routing problems with time windows are reported. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Geiger, M. J., & Wenger, W. (2007). On the interactive resolution of multi-objective vehicle routing problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4403 LNCS, pp. 687–699). Springer Verlag. https://doi.org/10.1007/978-3-540-70928-2_52
Mendeley helps you to discover research relevant for your work.