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Theoretical Foundations of CP-Based Lagrangian Relaxation

  • Conference paper
Principles and Practice of Constraint Programming – CP 2004 (CP 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3258))

Abstract

CP-based Lagrangian Relaxation allows us to reason on local substructures while maintaining a global view on an entire optimization problem. While the idea of cost-based filtering with respect to systematically changing objective functions has been around for more than three years now, so far some important observations have not been explained. In this paper, we prove a simple theorem that explains a variety of effects that are encountered in practice, the most counter-intuitive being the fact that suboptimal Lagrangian multipliers can have stronger filtering abilities than optimal ones.

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

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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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Editor information

Editors and Affiliations

  1. Clayton School of IT, Monash University, Australia

    Mark Wallace

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© 2004 Springer-Verlag Berlin Heidelberg

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Sellmann, M. (2004). Theoretical Foundations of CP-Based Lagrangian Relaxation. In: Wallace, M. (eds) Principles and Practice of Constraint Programming – CP 2004. CP 2004. Lecture Notes in Computer Science, vol 3258. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30201-8_46

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  • DOI: https://doi.org/10.1007/978-3-540-30201-8_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23241-4

  • Online ISBN: 978-3-540-30201-8

  • eBook Packages: Springer Book Archive

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