Duality in balance optimization subset selection

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

doi:10.1007/s10479-020-03513-y

Duality in balance optimization subset selection

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

Research output: Contribution to journal › Article › peer-review

Abstract

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 language	English (US)
Pages (from-to)	277-289
Number of pages	13
Journal	Annals of Operations Research
Volume	289
Issue number	2
DOIs	https://doi.org/10.1007/s10479-020-03513-y
State	Published - Jun 1 2020

Keywords

Duality
Linear programming
Optimization for causal analysis

ASJC Scopus subject areas

General Decision Sciences
Management Science and Operations Research

Online availability

10.1007/s10479-020-03513-y

Library availability

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AB - 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.

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KW - Optimization for causal analysis

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Duality in balance optimization subset selection

Abstract

Keywords

ASJC Scopus subject areas

Online availability

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