Towards a Closer Integration of Dynamic Programming and Constraint Programming

13 pages•Published: September 17, 2018

Steven Prestwich, Roberto Rossi, S. Armagan Tarim and Andrea Visentin

Abstract

Three connections between Dynamic Programming (DP) and Constraint Programming (CP) have previously been explored in the literature: DP-based global constraints, DP- like memoisation during tree search to avoid recomputing results, and subsumption of both by bucket elimination. In this paper we propose a new connection: many discrete DP algorithms can be directly modelled and solved as a constraint satisfaction problem (CSP) without backtracking. This has applications including the design of monolithic CP models for bilevel optimisation. We show that constraint filtering can occur between leader and follower variables in such models, and demonstrate the method on network interdiction.

Keyphrases: bilevel optimisation, constraint programming, dynamic programming, network interdiction

In: Daniel Lee, Alexander Steen and Toby Walsh (editors). GCAI-2018. 4th Global Conference on Artificial Intelligence, vol 55, pages 202-214.

Links:	https://easychair.org/publications/paper/hksH
	https://doi.org/10.29007/gscn

BibTeX entry

@inproceedings{GCAI-2018:Towards_Closer_Integration_Dynamic,
  author    = {Steven Prestwich and Roberto Rossi and S. Armagan Tarim and Andrea Visentin},
  title     = {Towards a Closer Integration of Dynamic Programming and Constraint Programming},
  booktitle = {GCAI-2018. 4th Global Conference on Artificial Intelligence},
  editor    = {Daniel Lee and Alexander Steen and Toby Walsh},
  series    = {EPiC Series in Computing},
  volume    = {55},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/hksH},
  doi       = {10.29007/gscn},
  pages     = {202-214},
  year      = {2018}}

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