{
  "id": 3015,
  "url": "https://arxiv.org/abs/2607.11725v1",
  "title": "Time-Lag-Aware Deep Reinforcement Learning for Flexible Job-Shop Scheduling in PPVC Module Factories",
  "summary": "Prefabricated prefinished volumetric construction moves most building work into module factories, whose production floor operates as a flexible job shop. A major complication is decisive: long post-operation time-lags caused by concrete curing, watertightness ponding tests, and paint drying, during which a module is blocked while its workstation stays free. On benchmark instances grounded in an official national prefabrication guidebook, these lags inflate even the optimal reference makespan by ",
  "authors": "Ziheng Zhang, Wei Zhang",
  "category": "research",
  "topics": "jobs-economy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-13T15:50:00.000Z",
  "fetched_at": "2026-07-14T16:11:46.979Z",
  "source_slug": "x-arxiv-cs-ai",
  "source_name": "arXiv cs.AI",
  "source_homepage": "https://arxiv.org/list/cs.AI/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/3015",
  "original_url": "https://arxiv.org/abs/2607.11725v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}