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Sparse Linear Surrogates for Interpretable Budget Allocation

2026/08/03 by Marc Goerigk, Michael Hartisch, Sebastian Merten
Mathematics · #math.OC

paper · pdf

arxiv created 2026/08/03 · arxiv updated 2026/08/04

Abstract

To address the demand for inherently interpretable optimization methods, we introduce novel linear surrogates for budget allocation problems. These surrogates consist of sparse linear rules that map instances to feature-based representations of solutions. We present an exact approach based on mixed-integer programming as well as a heuristic for their computation. The performance of both approaches is analyzed through computational experiments.

Citations