{
  "abstract": "In the home healthcare sector, patients often prefer familiar caregivers. Honoring these preferences can unbalance caregivers’ workloads, which can overload some caregivers and disrupt the day’s schedule. Patient cancellations, no-shows, emergencies, and caregiver delays and absences further disrupt schedules. This study proposes a four-objective mathematical model of the home healthcare scheduling and routing problem that jointly optimizes patient preference satisfaction, an operational caregiver burden index, travel distance, and workload balance; the index, built from duty time, patient acuity, and late visits, is a proxy, not a validated measure of burnout. The solution method combines NSGA-II with a local search procedure, and a dynamic extension re-optimizes the schedule when disruptions occur. The model is tested on 18 adapted Solomon instances spanning three scales and three distribution structures. A controlled ablation shows that optimizing the index lowers it in every instance (median change −25%, −15%, and −9% at 25, 50, and 100 patients, and −25% with seven caregivers on six 50-patient instances), but at the cost of 18%, 37%, and 39% more travel and, from 50 patients onward, worse patient preferences; it lowers the share of late visits but does not reduce overtime. NSGA-II is competitive with NSGA-III and MOEA/D. In 1080 simulated disruptions, re-optimization reduces travel, lateness, and overtime relative to keeping the plan, but it increases workload imbalance, does not lower the realized burden, and moves 9% to 11% of the patients to another caregiver (3% to 4% under keeping the plan).",
  "abstract_shown": true,
  "affiliations": [
    "Computer Science Department, College of Science, Northern Border University, Arar 91431, Saudi Arabia"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Radhia Zaghdoud"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/99z9kk6rac2sm.bib",
  "cited_by": 0,
  "doi": "10.3390/math14214028",
  "fulltext_url": null,
  "id": "99z9kk6rac2sm",
  "issns": [
    "2227-7390"
  ],
  "landing_url": "https://www.mdpi.com/2227-7390/14/21/4028",
  "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": "2026-11-04",
  "publisher": "MDPI AG",
  "ris": "https://research.draconitic.com/paper/99z9kk6rac2sm.ris",
  "sources": [
    {
      "first_seen": "2026-11-04T12:20:59Z",
      "native_id": "10.3390/math14214028",
      "source": "crossref",
      "url": "https://www.mdpi.com/2227-7390/14/21/4028"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "issn:2227-7390",
      "subfield": "general"
    }
  ],
  "title": "Balancing Efficiency, Patient Preference, and Operational Caregiver Burden in Dynamic Home Healthcare Scheduling: A Four-Objective NSGA-II Approach",
  "title_text": "Balancing Efficiency, Patient Preference, and Operational Caregiver Burden in Dynamic Home Healthcare Scheduling: A Four-Objective NSGA-II Approach",
  "type": "peer-reviewed",
  "updated_at": "2026-11-06T00:21:06Z",
  "url": "https://research.draconitic.com/paper/99z9kk6rac2sm",
  "venue": "Mathematics",
  "versions": []
}