{
  "abstract": "Fluid antenna systems (FASs) offer significant spatial flexibility, yet securing them against eavesdropping is critical for practical FAS deployment in military, satellite, and internet-of-things networks. Although large language model (LLM)-assisted genetic algorithms (LLM-GAs) can address this secure FAS port selection problem, whether further algorithmic improvement is possible warrants deeper investigation. To this end, we propose a memetic algorithm based on reflective evolution (ReEvo). Unlike the state-of-the-art LLM-GAs, which design only crossover or mutation operators with an LLM, our algorithm leverages an LLM to evolve dedicated crossover, mutation, and local-search operators offline. These operators are then embedded into a memetic search framework, thereby obviating any online LLM queries during execution. Simulation results at equal generation counts demonstrate that our proposed algorithm achieves a higher secure sum-rate than the conventional GA and the state-of-the-art LLM-GAs.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.10235",
  "author_total": 3,
  "authors": [
    {
      "name": "Hanyong Xu"
    },
    {
      "name": "Zhaolai Dang"
    },
    {
      "name": "Tong Zhang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/0wexr1r34re42.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.10235",
  "fulltext_url": null,
  "id": "0wexr1r34re42",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.10235",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.AI"
    ],
    [
      "arxiv",
      "cs.IT"
    ],
    [
      "arxiv",
      "math.IT"
    ],
    [
      "openalex",
      "2202|Antenna Design and Optimization"
    ]
  ],
  "openalex": "W7221032471",
  "pdf_url": "https://arxiv.org/pdf/2610.10235",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-26",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/0wexr1r34re42.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:35:40Z",
      "native_id": "2610.10235",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.10235"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.IT",
      "subfield": "general"
    }
  ],
  "title": "Beyond LLM-GA: Secure Fluid Antenna Systems with ReEvo-Designed Memetic Algorithm",
  "title_text": "Beyond LLM-GA: Secure Fluid Antenna Systems with ReEvo-Designed Memetic Algorithm",
  "type": "preprint",
  "updated_at": "2026-10-30T12:35:40Z",
  "url": "https://research.draconitic.com/paper/0wexr1r34re42",
  "venue": "arXiv",
  "versions": []
}