護士排班問題是指在醫療機構中有效安排護士的工作時間表，以確保有足夠的護理人力 覆蓋不同的需求。這是一個具有挑戰性的問題，因為護士排班需要考慮多個因素，包括護士 的技能水平、工作天數限制、法定休息時間和特殊要求等。在護士排班問題中，最主要的目 標是確保醫療機構能夠在每個班次中有足夠的護理人力，以提供高質量的護理照顧。同時， 排班系統還需要考慮護士的個人需求和偏好，例如平衡工作時間和生活平衡，避免過度疲勞 和減少排班衝突。 在解決護士排班問題時，方法包括傳統的手動排班和優化算法;傳統手動排班方法通常耗 時且容易出錯，且可能無法滿足複雜的排班需求，因此目前有許多研究著重於開發最佳化演 算法，以自動化方式對護士班表進行排班。優化演算法通常基於數學模型和演算法來解決護 士排班問題，這些方法將護士的技能、工作限制和需求等因素納入考慮，並根據特定的目標 函數進行排班優化。優秀的護士排班系統可以帶來多方面的好處，包括提高護理質量、增加 護士滿意度、降低成本和提升醫療機構的運營效率。因此，護士排班問題一直是醫療管理領 域和研究人員關注的重要課題，並且在過去幾十年中引起了廣泛的研究和開發新的排班方法 和系統。 然而對於護士之間的團隊合作，卻鮮少有人提及，有效的醫療團隊合作可以促進資訊共 享、有效的溝通和協作，從而提高患者護理的連續性和協調性。團隊成員之間的良好合作可 以減少錯誤和疏漏，確保患者的護理計劃得以順利執行，並能及時應對可能出現的問題和併 發症。因此在本研究中，在傳統護士排班問題之上，加入團隊合作的考量，希望班表不僅滿 足限制需求，還能夠加強護士之間的連結，提供更全面的醫療照護。我們也模擬了一些現實 的狀況，並與其他方法比較在這些情境下的表現，在結果中也顯示我們的方法再加入了團隊 合作的考量後，能夠比其他方法安排更好的團隊，並同時滿足更多護士的需求。

The nurse scheduling problem involves effectively organizing nurses’ work schedules in healthcare institutions to ensure sufficient nursing coverage for diverse demands. It is a challenging task that requires considering multiple factors, such as nurses’ skill levels, workday restrictions, statutory rest periods, and specific requirements. Solutions to the nurse scheduling problem include traditional manual scheduling and optimization algorithms. Consequently, significant research has focused on developing optimization algorithms to automate nurse scheduling. These algorithms incorporate mathematical models and algorithms to optimize the scheduling process by considering factors such as nurses’ skills and demands, while optimizing specific objective functions. An effective nurse scheduling system offers numerous benefits, including improved nursing quality, increased nurse satisfaction, cost reduction, and enhanced operational efficiency of healthcare institutions. However, teamwork among nurses is often overlooked in traditional nurse scheduling approaches.Strong teamwork among team members reduces errors and enables timely responses to issues and complications. Thus, in this study, we incorporate considerations of team teamwork into the traditional nurse scheduling problem. We conducted simulations under various realistic scenarios and compared the performance of our method with other approaches within these contexts. The results demonstrated that our approach, which incorporates team teamwork considerations, enables superior team arrangement and addresses more nurses’ needs compared to other methods.

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