本研究是結合基因演算法與線性規劃法兩種不同的最佳化方法於結構最佳化設計之研究。利用基
自演算法全域隨機搜尋的特性，並以亂數作全域隨機搜尋避免落入區域最佳解。接著使用基因演算法
求得之結果再利用逐次線性規劃法找尋是否有更佳解。本研究以ANSYS 有限元素分析軟體中的APDL
語法與FORTRAN 程式結合成一系統程式。並以五個不同範例執行結構最佳化設計，數值範例中將對
各種結構作分析與討論。範例中可驗證結合基因演算法與線性規劃法於結構之最佳化設計上可以得到
平錯的結果。 Genetic Algorithm (GA) system and Sequential Linear Programming (SLP) were used for structural
optimization in this study. The advantage of Genetic Algorithm is that it has multi-point search strategy
instead of one-point search to find the global optimum in a space. The ability of Genetic Algorithm is that it
can jump over the local optimum and obtain the global optimum. After the solution of Genetic Algorithm
was obtained, we can use Sequential Linear Programming to find whether there is a better solution. Since
sensitivity can provide the optimal search direction, the central difference method was used in sensitivity
analysis.
