本研究以一包裝材料印刷公司為例，探討零工式(Job-shop)生產系統，有若干工作站以及需加工的產品，在給定的廠房空間中安排這些工作站的位置，以達到最佳績效之設施規劃問題。傳統上的設施規劃問題多考慮固定產品需求，而案例公司的產品需求量具有變異性，方案的績效亦會隨之變化。且本研究問題之規劃方案數量眾多，加上績效評估困難的特性，使得傳統規劃方法難以應用。
　　本研究運用模擬最佳化的手法，考慮案例公司產品需求之變異，結合基因演算法產生、搜尋方案，以及模擬模式評估績效，以重複模擬處理輸入資料之隨機性，設法處理此設施規劃問題。依照案例公司需求，以最小化產品平均生產週期時間為目標，同時考慮SLP特有之活動關係，以及搬運路線之特殊限制條件，使規劃結果更接近實務情形。本問題求解方案數龐大，除了使用基因演算法進行解空間搜尋，同時利用最佳計算量分配(Optimal Computing Budget Allocation, OCBA)有效分配模擬資源，節省模擬時間。
　　本研究最後考慮因預測產品需求量變動造成不同的供需情境，提供數個建議初步規劃方案，並分析需求變異波動對於各方案績效的影響，做為案例公司執行後續細部設施規劃之參考。

第一章 緒論 10
1.1 研究背景與動機 10
1.2 研究目的 11
1.3 研究範圍 12
1.4 研究步驟 13
第二章 公司背景與問題特性 14
2.1 案例公司背景與產業特性 14
2.2 案例公司現行設施規劃方法 15
2.3 案例公司之問題特性 24
第三章 文獻回顧 26
3.1 設施規劃問題 26
3.1.1 工作站特性 26
3.1.2 靜/動態規劃 31
3.1.3 問題表示方法 32
3.1.4 求解方法 32
3.2 最佳化演算法應用 33
3.2.1 確定型解法 33
3.2.2 估計型解法 34
3.3 模擬最佳化 41
3.4 問題特性之相關研究 46
3.5 路徑演算法 47
3.6 小結 49
第四章 問題定義 50
4.1 問題描述 50
4.1.1 規劃區域資訊 50
4.1.2 產品資訊 51
4.1.3 工作站資訊 53
4.1.4 搬運器材資訊 53
4.2 問題定義與假設 54
4.3 特殊限制條件 56
4.3.1 進出口之限制條件 56
4.3.2 搬運距離之限制條件 57
4.3.3 棧板數變化之限制條件 58
第五章 研究方法 60
5.1 基因演算法 60
5.2 模擬最佳化架構 82
5.2.1 模擬模式建構 83
5.2.2 模式確認與驗證 86
第六章 實驗與分析 87
6.1 實驗一：模擬最佳化架構求解 87
6.2 實驗二：使用OCBA分配模擬資源 92
6.3 實驗三：需求變異分析 98
6.4 小結 109
第七章 結論與建議 110
7.1 結論 110
7.2 建議與未來方向 111
參考文獻 112

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