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Algorithms and Complexities of Matching Variants in Covariate Balancing

Author

Listed:
  • Dorit S. Hochbaum

    (Department of IEOR, University of California, Berkeley, Berkeley, California 94720)

  • Asaf Levin

    (Faculty of Industrial Engineering and Management, The Technion, Haifa 3200003, Israel)

  • Xu Rao

    (Department of IEOR, University of California, Berkeley, Berkeley, California 94720)

Abstract

Here, we study several variants of matching problems that arise in covariate balancing. Covariate balancing problems can be viewed as variants of matching, or b-matching, with global side constraints. We present here a comprehensive complexity study of the covariate balancing problems providing polynomial time algorithms, or a proof of NP-hardness. The polynomial time algorithms described are mostly combinatorial and rely on network flow techniques. In addition, we present several fixed-parameter tractable results for problems where the number of covariates and the number of levels of each covariate are seen as a parameter.

Suggested Citation

  • Dorit S. Hochbaum & Asaf Levin & Xu Rao, 2023. "Algorithms and Complexities of Matching Variants in Covariate Balancing," Operations Research, INFORMS, vol. 71(5), pages 1800-1814, September.
    • Handle: RePEc:inm:oropre:v:71:y:2023:i:5:p:1800-1814
    DOI: 10.1287/opre.2022.2286
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