近年來隨著原物料取得越來越困難以及原物料價格的上漲，如何有效地將原物料的使用價值發揮到最大，是相關產業所要面對的重要問題。探討加工生產業以及營建產業中，原物料經常遇到裁切之問題包含鋼板切割、壓克力板、玻璃裁切、木板…等，這些都是屬於二維平面切割的問題，如何使用將原物料的使用率發揮到最大、將切割後剩餘的材料降至最少是一個值得關注的課題。
近年來啟發式演算法的應用逐漸成熟，目前工程上許多複雜問題都可以藉由啟發式演算法進行求解。本研究所應用之自動調適生物共生演算法(Auto-tuning SOS)為一創新最佳化演算法[2]，Auto-tuning SOS是以生物共生演算法(SOS)為基礎，結合田口實驗方法及窗口移動搜尋兩種方法搜尋全域最佳解，經測試後發現此方法，具有提升搜尋效率，並且減少消耗時間以及資源的優勢。
本研究以解決二維平面切割的問題，並針對鋼板切割問題進行探討，以找出餘料最小之目標函數直。然後再與基因演算法(Genetic Algorithm, GA)、粒子群演算法(Particle Swarm Optimization, PSO)、生物共生演算法(Symbiotic Organisms Search, SOS)等演算法進行求解比較，找出適用於鋼板切割問題的最優良演算法。
經運算測試後得証，使用自動調適生物共生演算法在二維平面切割的問題時，可得出最佳之結果。

In recent years, it has become increasingly difficult to obtain raw materials and the price of raw materials has risen. How to effectively maximize the use value of raw materials is an important issue for related industries. In the processing industry and the construction industry, the original material often encounters cutting problems including steel plate, acrylic plates, glass, wooden plates, etc. These are all problems with 2D plane cutting.
The application of heuristic algorithms has gradually matured in recent years. Many current engineering problems can be solved by heuristic algorithms. Auto-tuning SOS is a new optimization algorithm based on the SOS and Self-tuning SOS, plus the Taguchi Methods and Sliding Window. After testing, Auto-tuning SOS was found to improve search efficiency and reduce the time spent and the advantages of resources.
This study solves the problem of 2D plane cutting combined with Auto-tuning SOS. Organism code consists of three parts, Box Packing Sequence, Vector of Box Orientations and Vector of Placement Heuristics. Compared with other algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Symbiotic Organisms Search (SOS)

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