手術預定開始時間問題在醫療領域中是一個重要的議題，其策略主要為如何 維持各績效之間的平衡，若醫院擁有良好的手術排程策略，將能有效地降低成本進而提高利潤。因此近年來，手術排程問題逐漸被重視且以各種不同的方式進行求解，而其中最重要的便是決定各手術的預定開始時間。本研究探討手術延遲時間、手術室閒置時間以及手術室超時共三個績效指標，並透過權重加成法整合至目標式。另外將透過決定手術預定開始時間區段以簡化問題求解難度。手術耗時屬於隨機性的因子，一般的數學模式難以處理這些具有隨機性因子的問題。因此本研究運用模擬最佳化發展了一種結合式演算法來求解手術排程問題中的預定開始時間組合。透過結合了多個不同的排序與選擇程序，針對現有之候選解集合，逐步地篩選進而挑選出最終解。另外由於績效指標之變異程度在醫療環境當中影響重大，本研究將排程總成本之變異數納入考量，希望藉由一變異數門檻值篩選出風險程度較低的排程，並利用主觀者的效用函數，將各績效指標整合，進而挑出最終解。在變異篩選的部分，本研究提供兩種篩選程序(VSP-R與VSP-NR)，分別可應用在具有參考系統以及門檻定值的情況下。透過結合式演算法，可以挑選出總成本變異數較小的手術預定開始時間組合。在變異數篩選當中，最終解之品質將會受到參考解或是門檻值設定所影響。在兩方法比較當中，VSP-R求解速率較慢但其在實際情況中較容易應用，而VSP-NR有較快的求解速率但其需要設定一確切的門檻值。在決定手術預定開始時間的部分，可以透過設定較長的時間區段長度，以利演算法在短時間內求得一個相對還不錯的最佳解。

We consider a stochastic optimization model for a surgical scheduling problem when there is a single operating room. The goal is to determine the optimal start times of multiple elective surgeries within a single day, where the term “optimal” is defined as the largest surgically related utility value while achieving the given threshold defined by the performance variation of a reference solution. The optimization model involves quantities, such as expectation and variance formulations, that are analytically intractable, which implies that traditional mathematical programming techniques cannot be directly applied. Therefore, we develop a combined approach which is a fully sequential procedure using variance screening procedure in the first phase, and then employing the multiple attribute utility theory to select the best solution in the second phase. The numerical experiments show that the proposed algorithm performs well in searching for a promising solution in a reasonable amount of time.

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