Here you find instance definitions and the best known solutions (to our knowledge) for the 1000 customer instances of Gehring & Homberger's extended VRPTW benchmark. The version reported here has a hierarchical objective: 1) Minimize number of vehicles 2) Minimize total distance. Distance and time should be calculated with double precision, total distance results are rounded to two decimals. Exact methods typically use a total distance objective and use integral or low precision distance and time calculations. Hence, results are not directly comparable.
Instance definitions (text)
Here you find a zip file with the 1000 customer instances.
Best known results for Gehring & Homberger's 1000 customer instances
The instance names in blue are hyperlinks to files with corresponding detailed solutions. They have all been checked by our solution checker. Note that many best known solutions do not have a reference to a peer reviewed publication. For these, important details on the solution algorithm, the computing time, and the experimental platform are probably not available. Further, there is no guarantee that the solutions have been produced without using external information, such as detailed solutions published earlier. We may later introduce two categories: 'properly published' and 'freestyle', the latter with no restrictions.
b: Detailed solution provided by BC4
BC4, Mirosław BŁOCHO, Zbigniew J. CZECH, "A parallel memetic algorithm for the vehicle routing problem with time windows". 3PGCIC 2013, 8th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing.
BSJ - Bjørn Sigurd Johansen, , DSolver 09-2004
CAINIAO - Zhu He, Longfei Wang, Weibo Lin, Yujie Chen, Haoyuan Hu ( ), Yinghui Xu, & VRP Team
LL - H. Li and A. Lim, "Large Scale Time-Constrained Vehicle Routing Problems: A General Metaheuristic Framework with Extensive Experimental Results," Submitted to Artificial Intelligence Review, 2001.
MB - Mester, D. and O. Bräysy (2005), “Active Guided Evolution Strategies for Large Scale Vehicle Routing Problems with Time Windows”. Computers & Operations Research 32, 1593-1614.
MB2 - Mester, D & O. Bräysy (2012). "A new powerful metaheuristic for the VRPTW”, working paper, University of Haifa, Israel.
MK - M. Koch, "An approach combining two methods for the vehicle routing problem with time windows", The solutions were presented at EURO and EURO XX Conference 2004.
NB - Jakub Nalepa, Miroslaw Blocho. "Co-operation in the Parallel Memetic Algorithm", International Journal of Parallel Programming 214, pp 1-28. http://dx.doi.org/10.1007/s10766-014-0343-4
NBC - Jakub Nalepa, Miroslaw Blocho, and Zbigniew J. Czech. "Co-operation schemes for the parallel memetic algorithm". In Roman Wyrzykowski, Jack Dongarra, Konrad Karczewski, and Jerzy Waniewski, editors, Parallel Processing and Applied Mathematics, Lecture Notes in Computer Science, pages 191–201. Springer Berlin Heidelberg, 2014. ISBN 978-3-642-55223-6. doi: 10.1007/978-3-642-55224-3 19.
NBD - Yuichi Nagata, Olli Bräysy, and Wout Dullaert (2010). A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windows. Comput. Oper. Res. 37, 4 (April 2010), 724-737.
PGDR - Eric Prescott-Gagnon, Guy Desaulniers and Louis-Martin Rousseau. A Branch-and-Price-Based Large Neighborhood Search Algorithm for the Vehicle Routing Problem with Time Windows. (2007)
Q - Quintiq. http://www.quintiq.com/optimization/vrptw-world-records.html .
RP - S. Ropke & D.Pisinger. "A general heuristic for vehicle routing problems", technical report, Department of Computer Science, University of Copenhagen.
SCR - Piotr Sielski (), Piotr Cybula, Marek Rogalski (), Mariusz Kok, Piotr Beling, Andrzej Jaszkiewicz, Przemysław Pełka. Emapa S.A (http://www.emapa.pl), "New methods of VRP problem optimization", unpublished research funded by The National Centre for Research and Development. project number: POIR.01.01.01.-00-0222/16.
WA - Ruud Wagemaker. MSc thesis in progress. Tilburg University.
WW - Witoslaw Wierzbicki. "Design and implementation of parallel programs with shared memory". Master of Science Thesis, University of Silesia, Sosnowiec, 2012.
VCGP - T. Vidal, T. G. Crainic, M. Gendreau, C. Prins. "A hybrid genetic algorithm with adaptive diversity management for a large class of vehicle routing problems with time-windows", Computers & Operations Research, Vol. 40, No. 1. (January 2013), pp. 475-489.