生產排程是生產作業管理中重要的一環，傳統的賣方市場中，生產排程強調的是如何以低成本、生產資源高稼動率的狀況下大量生產少數種類商品的流程式生產，而在買方市場中，基於滿足消費者需求的觀念，產品朝向多樣少量的零工式生產，不同產品競爭共同的資源，再加上生產環境的不確定性，令生產排程的問題複雜度大增，也使得零工式的生產排程的研究課題益發令人注意。
傳統作業研究的排程方法是在限制的條件下尋求最佳解(Optimal solution)，對於愈趨於複雜的排程問題而言，最佳解需花費大量計算時間與成本，而啟發式(Heuristic)方法則以較少的時間與計算過程去求得次佳解(Sub-optimal Solution)甚而最佳解；Hastings將啟發式方法分為作業導向的啟發法(Operation Oriented Heuristics, OOH )與工作導向的啟發法(Job Oriented Heuristics, JOH)兩類，OOH的方法常見於一般的派工法則，以尋找下一個在機器上加工作業為目標，而JOH的方法針對優先順序高的工作訂出其所有作業在機器上的加工時間後，再決定下一個工作的作業的加工計劃，相較於OOH，JOH更適用於訂單式生產的環境，以較直覺、可行且易實行的方式快速產生排程。
目前JOH的相關研究均著重於單一目標最佳化的排程方法，本研究提出一個整合模糊多目標法以同時考量定量與定性的排程因素，與灰色關聯分析法用以制定各工作的加工順序，建構一個以工作導向(Job Oriented)為考量的零工式生產排程系統，用以解決具有動態性、不確定性、統計波動、依存關係以及基於各種考量下彼此相衝突的多重目標的排程問題。
最後我們以VBA for Excel建構了以本研究方法為基礎的排程系統，並執行了八個不同工作與機器數組合的實驗，經由統計的假設與檢定，相較於其他方法，在滿足交期與其他限制下，本研究對於工作整體的加工時間縮減有較佳表現。

Scheduling is among the most important operation in production management. In the traditional seller’s market, scheduling emphasizes on the flow shop type, which specializes in high-volume, low-cost and high-utilization production. On the other hand, to match the needs of customers in the buyer’s market, scheduling focuses on the job shop type, which specializes in low-to-medium volume and resource-sharing production. Job shop scheduling problems become more complex under uncertain production environments due to the needs of quick response and closer due date, etc. Owing to the above reasons, researchers pay more attention to the study of job shop scheduling problems.
The scheduling approaches of conventional Operation Research try to find the optimal solution under resource constraints. The optimal solution costs a lot of computational efforts and yet sometimes impossible to get. Heuristic approaches use fewer efforts to get sub-optimal or sometimes even optimal solutions. Hastings divides heuristics of scheduling problems into two categories, the operation oriented heuristics, OOH, and the job oriented heuristics, JOH. OOH finds the most suitable operation to be processed for the machine. JOH first determines the priorities for all jobs and then schedule their operation sequences for each machine. In general, job shop scheduling with many orders prefers JOH than OOH.
Recent researches of JOH focus on scheduling of single objective. In this research, we propose a job shop scheduling system that integrates fuzzy multi-objective methods to consider both quantity and quality scheduling factors with Grey Relational Analysis that determines job priorities to effectively solve the scheduling problems with dynamic environment, uncertain situation, statistical fluctuations, dependent events, and conflict objectives.
We used the VBA for Excel to conduct the scheduling system based on our research and tested 8 kinds of experiments with different jobs and machines. By testing statistical hypotheses, our method is superior on reducing processing time of jobs.

摘 要 i
ABSTRACTii
誌 謝iii
目 次iv
表 目 錄vi
圖 目 錄vii
第一章 緒論1
1.1 研究動機1
1.2 研究目的2
1.3 研究範圍與限制3
1.4 研究方法與架構4
第二章 文獻探討6
2.1 排程問題的描述6
2.1.1 排程問題的分類6
2.1.2 排程的技術8
2.2 模糊理論15
2.2.1 模糊數15
2.2.2 語意變數17
2.2.3 模糊模型17
2.2.4 模糊理論於排程之應用與績效衡量21
2.3 灰色系統29
2.3.1 灰色系統理論與方法29
2.3.2 灰關聯分析32
2.4 工作導向的排程系統38
2.4.1 以工作為導向的啟發法39
2.4.2 以工作為導向的排程程序40
第三章 模糊多目標混合灰關聯之啟發式排程44
3.1 基本假設與架構44
3.2 工作評估的法則47
3.3 工作順序的訂定47
3.4 初始排程的制定51
3.5 最小化加工時間的調整53
3.6 緊急訂單的處理55
3.7 績效評估模式56
第四章 系統建構與實例探討58
4.1 系統建構與說明58
4.1.1工作資料編輯模組59
4.1.2排程規劃運算模組61
4.1.3排程結果輸出模組61
4.2 範例說明62
4.3 實驗驗證67
第五章 結論與建議71
參考文獻73

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