{
  "abstract": "We study robust optimization problems with decision-dependent information discovery under polyhedral uncertainty and continuous recourse. We first establish structural properties of the resulting min-max-min problem, including existence of solutions and a condition under which information discovery has no value. Then, we develop a heuristic approach that combines affine decision rules with scenario generation and show that its adversarial separation problem is NP-hard. Additionally, we introduce a sampling procedure to estimate solution quality without solving the overall problem to global optimality. Numerical experiments on knapsack and facility-location instances show that the method outperforms a K-adaptability approach recently proposed in the literature in terms of computation time while achieving comparable solution quality. Our approach is applicable to polyhedral uncertainty sets that can be expressed as Ξ = σ + -σ -: (σ + , σ -) ∈ Θ with a downward monotone polytope Θ.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "name": "Ugur Karabas"
    },
    {
      "name": "Henri Lefebvre"
    },
    {
      "name": "Michael Poss"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/a71zq02095qm5.bib",
  "cited_by": 0,
  "doi": null,
  "fulltext_url": null,
  "id": "a71zq02095qm5",
  "issns": [],
  "landing_url": "https://hal.science/hal-05784143v1",
  "language": "en",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "hal",
      "0.math"
    ],
    [
      "hal",
      "1.math.math-oc"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://hal.science/hal-05784143/document",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-07",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/a71zq02095qm5.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:50Z",
      "native_id": "hal-05784143",
      "source": "hal",
      "url": "https://hal.science/hal-05784143v1"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "hal:1.math.math-oc",
      "subfield": "optimisation-control"
    }
  ],
  "title": "Affine Decision Rules for Robust Optimization with Decision-Dependent Information Discovery",
  "title_text": "Affine Decision Rules for Robust Optimization with Decision-Dependent Information Discovery",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:50Z",
  "url": "https://research.draconitic.com/paper/a71zq02095qm5",
  "venue": "HAL",
  "versions": []
}