護士排班問題（Nurse Scheduling Problem, NSP）長期以來是醫療管理中的關鍵議題，傳統方法多以符合法規、平衡工作量與滿足個人偏好為主要目標。然而，在實務運作中這些方法往往忽略了團隊協作在臨床照護中的關鍵角色，導致排班結果雖形式上合理，實際運作中卻可能降低護理效率。此外，當遇到臨時人力變動或突發事件時，現行系統也難以快速做出調整，缺乏即時應變的彈性，進而加重第一線人員的壓力，甚至影響留任意願。
本研究提出一套具「團隊協作導向」與「隨時可行性」的排班模型，試圖改善現有的 NSP 模型在團隊穩定性與彈性運用上的不足。我們引入「溝通成本」（ComC）作為新型彈性約束限制，量化護理人員間的歷史合作熟悉度，以鼓勵安排熟悉成員於同一班別，進而提升團隊合作效率。模型採用多階段模擬退火架構，並搭配溫度驅動的動態權重調整策略，依不同階段強化團隊結構、提升排班品質與偏好微調，同時確保在任一階段中斷時皆能輸出符合法規和醫院規範的可行解。
實驗結果顯示本方法在維持護士偏好品質的同時，能有效降低排班中的溝通成本並穩定滿足所有硬性的約束條件，展現其於真實排班環境中的可行性與應用潛力。此研究提供一種兼顧人力彈性與團隊合作的智慧排班設計思維，為未來臨床人力調度系統發展提供參考。

The Nurse Scheduling Problem (NSP) has long been a key challenge in healthcare management. While traditional approaches focus on regulatory compliance, workload balance, and personal preferences, they often neglect the importance of team collaboration in clinical settings. As a result, seemingly reasonable schedules may reduce care efficiency. Moreover, existing systems lack the flexibility to respond quickly to staffing changes or emergencies, increasing frontline pressure and impacting staff retention.
This research proposes a scheduling method with “teamwork orientation” and “real-time feasibility” in an attempt to improve the existing NSP model in terms of team stability and flexibility. By introducing the “Communication Cost” (ComC) as a novel soft constraint to quantify the familiarity of nursing staff with each other’s history of cooperation, we can encourage the scheduling of familiar members in the same shift to enhance the efficiency of teamwork. The proposed method adopts a Multi-Phase Simulated Annealing framework with temperature-driven dynamic weighting to build team structures, improve schedule quality, and finetune nurses’ preferences while ensuring feasible solutions at any interruption point.
Experimental results show that the proposed method effectively reduces communication costs, maintains preference quality, and consistently satisfies all hard constraints, demonstrating its feasibility and potential application in real scheduling environments. This study provides a smart scheduling design concept that takes into account the flexibility of staffing and teamwork and provides a reference for the future development of clinical staff scheduling systems.

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