自由經濟引爆全球化的浪潮，為滿足全球化的需求，區域供應鏈和全球供應鏈於焉產生，企業為取得成本最佳化的規模經濟以及最佳核心能力的專注策略，其生產活動已由過去的單一工廠生產演變成跨國家、多工廠的生產模式。更為了滿足客戶及擴張策略之需求，往往透過擴廠或併購取得新工廠，快速擴大產能，亦逐漸的由單一廠區轉變為多廠區生產模式。因此各生產商必須完善多廠區的生產規劃，使各企業每個廠區的生產資源與產品配置最佳化，產生最佳生產模式來降低生產成本，並透過科學管理手法，創造生產效益，維持市場競爭力。
本研究利用實際LED工廠的數據來進行探討，個案公司面臨之問題為產量分配，為求成本最小化，此投片規劃主要為解決多廠區多階層之多產品分配問題，依據數學規劃之特性，包含MPS需求量、產品廠區階層限制、產能上下限、生產變動成本及運輸成本，額外加入生產目標時間限制 (包含生產製程時間與運輸時間)以解決規劃人員擔心廠間運送導致無法達成總生產完工時間，將更為實務使用。
並且利用遺傳演算法結合線性規劃解決求解效率問題，別於一般遺傳演算法隨機搜尋解的特性，在演算過程中，皆將非可行解排除在外，保證過程中產生的解皆為可行解，另外再加入低成本廠區優先分配機制，當其滿足產能上限後，再往次低成本廠區分配，此兩方法可增加遺傳演算法之搜尋效率並且使得演化結果更易趨於最佳解，而非區域最佳解，達成本研究最終目標為最低生產成本的最佳化配置。

The thesis uses actual data from the LED industry to do the analysis. The purpose of the research is to allocate capacity efficiently and minimize cost. The production plan is mainly intended to solve the allocation problem for multi-site and multi-stage production plans. According to the mathematical programming characteristics, such as MPS demand, the limitation of each production site, the upper and lower capacity bounds, production variable costs, transportation costs, and limits to the target production time, are formulated in the MP model for the case firm. A GA (genetic algorithm) is implemented to solve the proposed model and the near-optimal of the problem can be acquired using the GA. Furthermore, a sensitivity analysis is conducted to verify the parameters of the GA and it is found that the value set of the parameters can facilitate reaching the near-optimal solution.

參考文獻
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