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A predictive–prescriptive framework for operating room scheduling: Transformer-based duration estimation and system-coupled robust multi-resource optimization
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DOI：10.1016/j.eswa.2026.134018.png)
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Abstract
En 中文
<ul class="list">
<li class="react-xocs-list-item"><span class="list-label">•</span><span class="list-content">
<div class="u-margin-s-bottom" id="p0002">
A BioBERT-based predictive–prescriptive OR framework is proposed.
</div></span></li>
<li class="react-xocs-list-item"><span class="list-label">•</span><span class="list-content">
<div class="u-margin-s-bottom" id="p0003">
A coupled MICQP model with PACU and surgeon fatigue constraints is developed.
</div></span></li>
<li class="react-xocs-list-item"><span class="list-label">•</span><span class="list-content">
<div class="u-margin-s-bottom" id="p0004">
Interval-based robust surgical durations are introduced for uncertainty.
</div></span></li>
<li class="react-xocs-list-item"><span class="list-label">•</span><span class="list-content">
<div class="u-margin-s-bottom" id="p0005">
The OR efficiency–robustness trade-off under uncertainty is quantified.
</div></span></li>
<li class="react-xocs-list-item"><span class="list-label">•</span><span class="list-content">
<div class="u-margin-s-bottom" id="p0006">
Resilient schedules eliminating PACU congestion and surgeon overload are generated.
</div></span></li>
</ul>
Keywords:
Operating room scheduling
Predictive–prescriptive analytics
Robust optimization
Transformer neural networks
Perioperative planning
Multi-objective optimization
Journal
IF:
7.5
Papers:
2.9W
Citations:
10.2W
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