Abstract
In this paper, we describe a Constraint Programming (CP) route finding application for a container transportation company. Mathematically, this amounts to finding the k shortest paths in a directed graph. However the nature of the business constraints rule out known algorithms such as Dijkstra’s. Indeed, one cannot unfold all constraints into a directed graph as the resulting graph would be too large. Given an origin and destination (two places), the problem is to decide which ships should be used (routes), and when and where the containers should be loaded from one ship to another (connections), while satisfying many business rules specified by the transportation company. The CP model described in this paper is quite simple, it doesn’t use any specialized constraints, but it is surprisingly effective. Queries for the best route are answered in a matter of a second or fraction of a second, although the problem is very large: around 900 places, 2,300 routes, 22,000 connections and 4,200 business rules. The system gracefully handles 100,000 requests a day on a single server.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
IBM ILOG CPLEX Optimization Studio, http://www-01.ibm.com/software/integration/optimization/cplex-optimization-studio/
Bistarelli, S., Montanari, U.: Soft constraint logic programming and generalized shortest path problems. Journal of Heuristics 8(1), 25–41 (2002)
Dooms, G., Deville, Y., Dupont, P.: CP(Graph): Introducing a graph computation domain in constraint programming. In: van Beek, P. (ed.) CP 2005. LNCS, vol. 3709, pp. 211–225. Springer, Heidelberg (2005)
Van Hentenryck, P., Lustig, I., Michel, L., Puget, J.-F.: The OPL optimization programming language. MIT Press, Cambridge (1999)
IBM. IBM ILOG CPLEX Optimization Studio documentation. volume 8:1. IBM (2010), http://publib.boulder.ibm.com/infocenter/cosinfoc/v12r2/index.jsp
Lhomme, O., Régin, J.-C.: A fast arc consistency algorithm for n-ary constraints. In: AAAI 2005 (2005)
Puget, J.-F.: Constraint programming next challenge: Simplicity of use. In: Wallace, M. (ed.) CP 2004. LNCS, vol. 3258, pp. 5–8. Springer, Heidelberg (2004)
Quesada, L., Roy, P.V., Deville, Y., Collet, R.: Using dominators for solving constrained path problems. In: PADL, pp. 73–87 (2006)
Refalo, P.: Impact-based search strategies for constraint programming. In: Wallace, M. (ed.) CP 2004. LNCS, vol. 3258, pp. 557–571. Springer, Heidelberg (2004)
Régin, J.-C.: Generalized arc consistency for global cardinality constraint. In: Proceedings of the 13th National Conference on AI (AAAI/IAAI 1996), vol. 1, pp. 209–215. AAAI Press / The MIT Press (1996)
Sellmann, M.: Cost-based filtering for shorter path constraints. In: Rossi, F. (ed.) CP 2003. LNCS, vol. 2833, pp. 694–708. Springer, Heidelberg (2003)
Wallander, M.P., Szymanek, R., Kuchcinski, K.: CP-LP hybrid method for unique shortest path routing optimization. In: Proceedings of the International Network Optimization Conference (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lefebvre, M.P., Puget, JF., Vilím, P. (2011). Route Finder: Efficiently Finding k Shortest Paths Using Constraint Programming. In: Lee, J. (eds) Principles and Practice of Constraint Programming – CP 2011. CP 2011. Lecture Notes in Computer Science, vol 6876. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23786-7_6
Download citation
DOI: https://doi.org/10.1007/978-3-642-23786-7_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23785-0
Online ISBN: 978-3-642-23786-7
eBook Packages: Computer ScienceComputer Science (R0)