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International Conference on Principles and Practice of Constraint Programming

CP 2003: Principles and Practice of Constraint Programming – CP 2003 pp 694–708Cite as

Cost-Based Filtering for Shorter Path Constraints

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2833))

Abstract

Many real world problems, e.g. in personnel scheduling and transportation planning, can be modeled naturally as Constrained Shortest Path Problems (CSPPs), i.e., as Shortest Path Problems with additional constraints. A well studied problem in this class is the Resource Constrained Shortest Path Problem. Reduction techniques are vital ingredients of solvers for the CSPP, that is frequently NP-hard, depending on the nature of the additional constraints. Viewed as heuristics, until today these techniques have not been studied theoretically with respect to their efficiency, i.e., with respect to the relation of filtering power and running time. Using the concepts of Constraint Programming, we provide a theoretical study of cost-based filtering for shorter path constraints on acyclic, on undirected and on directed graphs that do not contain negative cycles.

This work was supported by the Intelligent Information Systems Institute, Cornell University (AFOSR grant F49620-01-1-0076).

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Author information

Authors and Affiliations

  1. Department of Computer Science, Cornell University, 4130 Upson Hall, Ithaca, NY, 14853, USA

    Meinolf Sellmann

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  1. Meinolf Sellmann
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Editors and Affiliations

  1. Dipartimento di Matematica Pura ed Applicata, Università di Padova, Via Trieste 63, 35121, Padova, Italy

    Francesca Rossi

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Sellmann, M. (2003). Cost-Based Filtering for Shorter Path Constraints. In: Rossi, F. (eds) Principles and Practice of Constraint Programming – CP 2003. CP 2003. Lecture Notes in Computer Science, vol 2833. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45193-8_47

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  • DOI: https://doi.org/10.1007/978-3-540-45193-8_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20202-8

  • Online ISBN: 978-3-540-45193-8

  • eBook Packages: Springer Book Archive

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