{
  "abstract": "Port authorities must commit service capacity before monthly vessel demand is known. This study develops a multiobjective linear programming model based on Bertsimas–Sim Γ-robustness that jointly determines lower-cost regular capacity and higher-cost surge capacity. Monthly vessel-call uncertainty is represented by a budgeted uncertainty set, while an independent full-stress constraint imposes a minimum service level when all modeled upward deviations occur. A lexicographic ε-constraint procedure generates Pareto-optimal cost–shortage policies, and a balanced policy is selected by distance to the ideal point. The model is evaluated using 2020 data from 28 Chilean maritime authorities and validated with 2018–2022 data. At Γ = 0.10, the balanced policy allocates 647.0 regular and 207.5 surge units and achieves 98.41% full-stress service, with CostIdx 21% above the minimum-cost policy. The 15% deviation matches the historical year-ahead bound, and Γ = 0.10 is the smallest tested budget meeting the 95% out-of-sample target in three of four transitions. Full-stress reliability is the main CostIdx driver, whereas the base-capacity quantile mainly determines the capacity mix. Among alternatives meeting the same full-stress standard, the proposed model has the lowest CostIdx without requiring an assumed demand distribution.",
  "abstract_shown": true,
  "affiliations": [
    "Departamento de Ingeniería Industrial, Universidad Tecnológica Metropolitana, Santiago 7800002, Chile",
    "Departamento de Ingeniería Industrial y de Sistemas, Facultad de Ingeniería, Universidad de Tarapacá, Arica 1010069, Chile"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Claudia Durán",
      "orcid": "0000-0002-0903-4333"
    },
    {
      "affs": [
        1
      ],
      "name": "Amir Karbassi Yazdi",
      "orcid": "0000-0001-9436-5833"
    },
    {
      "affs": [
        0
      ],
      "name": "Sebastián Bastías"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/1vft2n0nf3vr2.bib",
  "cited_by": 0,
  "doi": "10.3390/math14213970",
  "fulltext_url": null,
  "id": "1vft2n0nf3vr2",
  "issns": [
    "2227-7390"
  ],
  "landing_url": "https://www.mdpi.com/2227-7390/14/21/3970",
  "language": null,
  "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": [],
  "openalex": null,
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-30",
  "publisher": "MDPI AG",
  "ris": "https://research.draconitic.com/paper/1vft2n0nf3vr2.ris",
  "sources": [
    {
      "first_seen": "2026-10-31T00:20:46Z",
      "native_id": "10.3390/math14213970",
      "source": "crossref",
      "url": "https://www.mdpi.com/2227-7390/14/21/3970"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "issn:2227-7390",
      "subfield": "general"
    }
  ],
  "title": "Multiobjective Γ-Robust Port Service-Capacity Planning Under Demand Uncertainty: Evidence from Chilean Vessel Movements",
  "title_text": "Multiobjective Γ-Robust Port Service-Capacity Planning Under Demand Uncertainty: Evidence from Chilean Vessel Movements",
  "type": "peer-reviewed",
  "updated_at": "2026-11-01T00:20:44Z",
  "url": "https://research.draconitic.com/paper/1vft2n0nf3vr2",
  "venue": "Mathematics",
  "versions": []
}