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100 customers
Here you find instance definitions and best known solutions for the 100 customer instances of Solomon's VRPTW benchmark problems from 1987. 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 monolithic total distance objective and use integral or low precision distance and time calculations. Hence, results are not directly comparable.
By clicking on an instance name in blue, you will open a file with a specification of the detailed solution.
Instance definitions (text)See Solomon's web page http://web.cba.neu.edu/~msolomon/problems.htm . As a backup, you will find a zip-file with the 100 instance definitions here. Best known solution values
See Solomon's web page http://web.cba.neu.edu/~msolomon/problems.htm . A few new results have been added in the updated table below.
b: Detailed solution by Bauke Conijn, TU EindhovenNB!Earlier, slightly better total distance values were reported for instances R101, R104, R106, R110, R208, R210, RC201, RC204, and RC205. These values were produced using lower precision arithmetic. We are grateful to Bauke Conijn of TU Eindhoven for pointing this out, and for providing us with correct values and detailed solutions for these instances. All detailed solutions have been checked by our solution checker. Some of the detailed solutions were taken from the website of Z. J. Czech. We also thank David Mester for giving us details on how the early results were produced, and for providing us with revised values and detailed solutions that were produced using double precision arithmetic. The solutions and values from the two sources coincide. We know that several other authors have produced solutions with the same values. References
LLH - H. Li, A. Lim, and J. Huang, "Local Search with Annealing-like Restarts to Solve the VRPTW," Working Paper, Department of Computer Science, National University of Singapore, 2001. SAM::OPT - Hasle G., O. Kloster: Industrial Vehicle Routing Problems. Chapter in Hasle G., K-A Lie, E. Quak (eds): Geometric Modelling, Numerical Simulation, and Optimization. ISBN 978-3-540-68782-5, Springer 2007. WL - Woch M., Łebkowski P.: Sequential Simulated Annealing for the Vehicle Routing Problem with Time Windows. Decision Making in Manufacturing and Services, vol. 3, no. 1-2., s. 87-100, 2009. |
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