彩色濾光片的高度客製化產品特性以及TFT-LCD產業的「零庫存」管理潮流下，每日依客戶需求進行生產排程的變更已成為常態。若再考量新產品的導入，生產排程變更的次數勢必更加頻繁。如何在複雜的彈性零工式排程中，快速求得有效解，成為專業彩色濾光片廠的一大挑戰。本論文提出「混合基因演算及資料探勘法」來達到快速求解彈性零工式排程的目的。本方法的基本策略，主要是將彈性零工式排程問題分成三個步驟來處理，首先，利用「基因演算法」來求解工廠現有實際的訂單需求案例，接著利用「分群法」進行訂單需求案例分群，最後以「決策樹」法找出訂單需求案例中各產品數量配比與排程間的關係，並定義其對應規則。透過本研究方法所建構之排程知識可讓排程者不須再透過任何演算工具，只須透過對應規則表即可快速獲得不錯的排程解。實驗結果上也證實混合基因演算及資料探勘法在類別70群因子下，其求解結果與基因演算法相近。

CF is a high custom-made product. It’s a routine work to change scheduling plan frequently to fit every customer’s delivery time especially in a tendency towards JIT management in the TFT-LCD manufacturing. It becomes a challenge to plan an efficient scheduling rapidly in flexible job shop. To solve this difficult problem, this study proposed one method that is called “Hybriding genetic algorithm and data mining methods”. This method contains there main steps. First, we create many order cases and deal with them by genetic algorithm method. Second, we use k-means method to classify all the order cases and further, find out the best solution of every cluster. Lastly we look for relations between cases and solutions and transform the relations into a rule chart. A rule chart will help us to find a solution rapidly to every new case.

張文豪（民91）。李克特式量表、分群方法與分群群數關係之研究。國立成功大學工業管理研究所碩士論文，未出版，台南市。
蔡杭助（民91）。結合基因演算法與離散事件模擬求解即時性平行機台之派工規劃問題。國立成功大學製造工程研究所碩士論文，未出版，台南市。
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