Algorithm Selection in VRP
A research project in collaboration with the Group on Computational Logistics and DBAI Group of Technical University of Vienna. The aim of the project is to develop and experiment with algorithm selection on VRP solving methods. Two publications will be produced, one for preliminary research on using state-of-the art, freely available CVRP solvers, and second outlining a VRP hyperheuristic with algorithm selection, runtime prediction, and parameter tuning.
This wiki will hold misc. notes of the project.
For example list of other people working on the same problem.
Notes of the relevant literature.
And so on…
- Pablo Garrido
He has done some work with VRP hyperheuristics when working with the Department
of Computer Science, Universidad Técnica Federico Santa María, Chile. Pablo
has published few papers of applying hyper-heuristic approach to solving
vehicle routing problems (esp. DVRPs). He also has published the source code
of the hypeheuristic CVRP solver. In the past he has worked together with
María-Cristina Riff and Elizabeth Montero, who in turn have done some parameter
tuning comparisons on TSPs (in fact the REVAC implementation came from them).
Currently Pablo is working as a Ph. D. student in Computer Science at
Universität des Saarlandes / Max-Planck-Institut für Informatik, Saarbrücken, Germany.
P. Garrido and C. Castro. A Flexible and Self-Adaptive Hyper-heuristic Approach for (Dynamic) Capacitated Vehicle Routing Problem. Fundamenta Informaticae 119(1), 29-60, 2012.
P. Garrido and M.-C. Riff. DVRP: A Hard Dynamic Combinatorial Optimisation Problem tackled by an Evolutionary Hyper-heuristic. In J. Heuristics 16(6), 795-834, 2010.
P. Garrido, C. Castro and E. Monfroy. Towards a flexible and adaptable hyperheuristic approach for VRPs. In IC-AI 2009, 311-317, CSREA, 2009.
P. Garrido and C. Castro. Stable solving of CVRPs using hyperheuristics. In GECCO 2009, 255-262, ACM, 2009.
- Pablo Garrido