Abstract
The Vehicle Routing Problem with Time Windows (VRPTW) is one of the most important and widely studied NP-hard combinatorial optimization problems in the operations research literature. The problem calls for the determination of a minimum-cost set of routes for a fleet of identical vehicles with limited capacities to serve a set of customers that have a given demand and an associated time window in which they can be visited. Due to its computational complexity, VRPTW can only be solved by exact methods for instances of moderate size [2]. However, a large number of successful metaheuristic solution methods have been proposed, which are able to produce high-quality solutions for reasonably-sized instances in limited time. For an extensive review, the reader is referred to [5, 3].
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References
R. Baldacci. Personal Communication, 2010.
R. Baldacci, E. Bartolini, A. Mingozzi, and R. Roberti. An exact solution framework for a broad class of vehicle routing problems. Computational Management Science, 7(3): 229–268, 2010.
Olli Bräysy and Michel Gendreau. Vehicle routing problem with time windows, Part II: Metaheuristics. Transportation Science, 39(1): 119–139, 2005.
J. F. Cordeau, G. Desaulnier, J. Desrosiers, M. Solomon, and F. Soumis. The VRP with time windows. In Paolo Toth and Daniele Vigo, editors, The vehicle routing problem. Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, 2001.
Michel Gendreau, Jean-Yves Potvin, Olli Bräysy, Geir Hasle, and Arne Løkketangen. Meta-heuristics for the vehicle routing problem and its extensions: A categorized bibliography. In Bruce L. Golden, editor, The Vehicle Routing Problem: Latest Advances and New Challenges, chapter 1, pages 143–169. Springer, 2008.
Fred Glover and Fred Laguna. Tabu Search. Kluwer, 1997.
M. W. P. Savelsbergh. Local search in routing problems with time windows. Annals of Operations Research, 4(1): 285–305, 1985.
M.W.P. Savelsbergh. An efficient implementation of local search algorithms for constrained routing problems. European Journal of Operational Research, 47(1): 75–85, 1990.
Michael Schneider, Christian Doppstadt, Bastian Sand, Andreas Stenger, and Michael Schwind. A vehicle routing problem with time windows and driver familiarity. In Seventh Triennial Symposium on Transportation Analysis, Tromso, Norway, 2010.
Michael Schneider, Christian Doppstadt, Andreas Stenger, and Michael Schwind. Ant colony optimization for a stochastic vehicle routing problem with driver learning. In IEEE Congress on Evolutionary Computation, Barcelona, Spain, 2010.
Paolo Toth and Daniele Vigo, editors. The vehicle routing problem. Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, 2001.
Toth, Paolo and Vigo, Daniele. The granular tabu search and its application to the vehicle-routing problem. INFORMS Journal on Computing, 15(4): 333–346, 2003.
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Doppstadt, C., Schneider, M., Stenger, A., Sand, B., Vigo, D., Schwind, M. (2011). Graph Sparsification for the Vehicle Routing Problem with Time Windows. In: Hu, B., Morasch, K., Pickl, S., Siegle, M. (eds) Operations Research Proceedings 2010. Operations Research Proceedings. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20009-0_36
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DOI: https://doi.org/10.1007/978-3-642-20009-0_36
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