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Column Generation with Domain-Independent Dynamic Programming

Authors Ryo Kuroiwa , Edward Lam

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LIPIcs.CP.2026.37.pdf
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Subject Classification

ACM Subject Classification
  • Computing methodologies → Modeling methodologies
  • Theory of computation → Dynamic programming
  • Theory of computation → Mathematical optimization
Keywords
  • Modelling & Modelling Languages
  • Dynamic Programming
  • Operations Research & Mathematical Optimisation

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Abstract

Column generation and branch-and-price (B&P) are leading mathematical optimization methods for large-scale exact optimization, iterating between solving a master problem and a pricing problem. Due to the difficulty of discrete optimization, high-performance column generation often relies on a custom pricing algorithm built specifically to exploit the problem’s structure. This bespoke nature of the pricing solver makes column generation a problem-specific method and hinders the use of generic implementations across a wide range of problems. We show that domain-independent dynamic programming (DIDP), a model-based paradigm for dynamic programming, can be used as a generic pricing solver. We develop new modeling features and a solving algorithm for DIDP to achieve better performance in typical pricing problems. We demonstrate that in four problem classes, our implementations of B&P, with pricing by DIDP, empirically outperform an existing automated B&P solver and B&P with pricing by mixed-integer programming or constraint programming.

Cite As Get BibTex

Ryo Kuroiwa and Edward Lam. Column Generation with Domain-Independent Dynamic Programming. In 32nd International Conference on Principles and Practice of Constraint Programming (CP 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 379, pp. 37:1-37:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/LIPIcs.CP.2026.37

Author Details

Ryo Kuroiwa
  • Principles of Informatics Division, National Institute of Informatics, Tokyo, Japan
  • The Graduate University for Advanced Studies, SOKENDAI, Kanagawa, Japan
Edward Lam
  • Department of Data Science and Artificial Intelligence, Monash University, Melbourne, Australia

Funding

  • Kuroiwa, Ryo: JSPS KAKENHI grant number JP25K24378
  • Lam, Edward: Australian Research Council, grant DE240100042

Supplementary Materials

References

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