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改良式遺傳演算法應用於成衣加工裁片搬運距離最小化之研究

A Study on Minimizing the Moving Distance for Cutting Pieces of Apparel Manufacturing Process with the Improved Genetic Algorithm

摘要


少量多款的成衣生產趨勢使機器設備及人員常隨之變動,良好的機器佈置環境與物料搬運路線成爲降低生產成本的重要課題,但縫製生產線的機器佈置常由現場主管依經驗直覺人工安排,優劣不易掌控。成衣生產爲有序加工,本研究應用從至圖、先行關係圖與矩陣,計算製程中裁片搬運距離,爲解決因工序數量大而增加有序搜索時間及難度,以改良式遺傳演算法將支線序列模組化,減少有序搜尋組數,結合階層式遺傳演算法及有序遺傳演算法觀念,用控制基因來控制模組基因,使模組基因對應之有序參數基因具有遞增及遞減序列。爲驗證本研究建構之改良式遺傳演算法可快速找到較佳機器佈置排序,本文以成衣廠最常使用之直線型或U型機器佈置,用不同的實例驗證結果,均有效縮短裁片搬運距離,改善效能達一至三成,不僅符合有序加工限制條件,同時具有隨機廣域搜尋及多處同時搜尋最佳解的優點,增加演算效能,縮短裁片搬運距離,提高生產效率。

關鍵字

成衣 機器佈置 遺傳演算法

並列摘要


The tendency of apparel clothes has shifted to the manufacturing of a small amount of a large variety of styles. The machines, equipment and the labor involved have to be adjusted accordingly. While reducing the time spent in moving the cutting pieces, the labor load, as well as the moving distance, we have to also keep in mind the convenience and flexibility of administration. The experience of the administrators of apparel factory is different from person to person whose performance could not be the best. Knowing the manufacturing of apparel is an order-based manufacturing processes, this study proposes the improved genetic algorithm, combined with order-based genetic algorithm and hierarchical genetic algorithm concept. It is control genes to control modular genes and to increase or decrease mapping parametric genes. The improved genetic algorithm in this study accelerate search quickly to get a better machines layout. The actual examples included prove that the application of the improved genetic algorithm helps us to find a better order arrangement of the machines. It not only reduces the moving distance of the cutting pieces, but it increases the manufacturing effects as well.

並列關鍵字

apparel machine layout genetic algorithms

參考文獻


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