臺灣博碩士論文加值系統

產線平衡問題是製造系統中經常碰到的問題，故為了使得產線系統能維持一定水準的生產率就必須同時考慮到多個目標，但在實務上這些目標未必是確定性的，因此模糊多目標產線平衡問題便產生。在傳統的數學模式中大都是已指定目標為考量，進而建立模式以解決問題提升目標品質，故難以建構這樣複雜的問題。在本研究中運用模糊多目標分段線性規劃模式將產線平衡問題中之四個目標，分別為最小化總完工時間、最小化工作站數、最小化工作站平滑度與最大化產品利潤之多目標問題轉換成單一目標，並使用分段線性隸屬函數進行計算所得結果以滿意程度表示，最後舉出案例進行驗證。而當案例規模愈加複雜，以窮舉法之數學規劃模式計算將會耗費大量的時間，造成低的求解效率。故本研究提出遺傳人工免疫演算法求解規模複雜之問題，利用演算法的特性提升求解的品質與效率。實務的環境經常處於不確定的、目標亦是含糊的，故本研究的目的在於幫助決策者不帶主觀與偏激的方式，客觀的考量整體問題並保有彈性決策行為外，做出滿意的決策。

Assembly line balancing problem is often encountered in a manufacturing system. In order to maintain a certain level of production rate, several objectives need to be considered at the same time. However, these objectives are not necessarily certain in real environments, and thus, a fuzzy multiple objective assembly line balancing problem （FMOALBP） is present. In traditional mathematical models, a single objective is considered, and the establishment of a model is to promote the quality of the objective. Therefore, such a model cannot solve a complicated problem. In this paper, a fuzzy multi-objective piecewise linear model for the assembly line balancing problem is applied, and there are four objectives: minimizing cycle time, minimizing the number of workstations, minimizing workload smoothness, and maximizing product profits. This multiple-objective model is converted into a single-objective model, and the piecewise linear membership function is used to calculate the satisfaction degree. A case study is presented to examine the model. And when case size is complicated, exhaustive enumeration become impractical to application. Therefore, heuristic may be necessary to solve the problem. In this paper, genetic artificial immune systems algorithm is constructed for solving large-scale scheduling problem and utilizes it to improve efficiency and quality of solution. In a real practice environment, uncertain condition and fuzzy objective are often present. The purpose of this paper is to help decision makers consider the overall problem objectively and then make satisfactory decisions.

摘要 i
ABSTRACT ii
目錄 iii
致謝 iv
表目錄 v
圖目錄 vi
一、緒論 1
1.1研究背景與動機 1
1.2研究目的 2
1.3研究流程 2
二、文獻探討 4
2.1生產線平衡問題 4
2.1.1生產線 4
2.1.2生產線平衡問題分類 6
2.2模糊多目標問題 12
2.3啟發式演算法 14
三、研究方法 18
3.1研究假設與符號 18
3.2多目標線性模型建構 19
3.3建構模糊多目標規劃之數學模式 21
3.4建構遺傳人工免疫演算法 24
四、案例研究 28
4.1案例 28
4.2案例一敘述 29
4.2.1初始執行結果 30
4.2.2驗證模糊多目標分段線性規劃模式 31
4.2.3案例分析 34
4.2.4驗證遺傳人工免疫演算法 38
4.3案例二模糊多目標分段線性規劃模式計算結果 40
4.4案例二遺傳人工免疫演算法計算結果 42
4.5案例三遺傳人工免疫演算法計算結果 44
五、結論與建議 48
參考文獻 50

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