Duality in balance optimization subset selection

Hee Youn Kwon, Jason J. Sauppe, Sheldon H. Jacobson

Research output: Contribution to journalArticlepeer-review


In this paper, we investigate a specific optimization problem that arises in the context of Balance Optimization Subset Selection (BOSS), which is an optimization framework for causal inference. Most BOSS problems can be formulated as mixed integer linear programs. By relaxing the integrality constraints so that fractional contributions of control units are permitted, a linear program (LP) is obtained. Properties of this LP and its dual are investigated and a sensitivity analysis is conducted to characterize how the objective value changes as the covariate values are perturbed.

Original languageEnglish (US)
Pages (from-to)277-289
Number of pages13
JournalAnnals of Operations Research
Issue number2
StatePublished - Jun 1 2020


  • Duality
  • Linear programming
  • Optimization for causal analysis

ASJC Scopus subject areas

  • General Decision Sciences
  • Management Science and Operations Research


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