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。利用基因演算法全域隨機搜尋的特性，將結構最佳化問題轉換為適存函數，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，逐次線性規劃法則採用中心差分法計算結構靈敏度以加快程式收斂之效率。 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。並以七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，分別以結構輕量化設計或提高結構之第一自然振動頻率為目的。範例中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不錯的結果。 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. A systematic program which combined APDL of ANSYS with FORTRAN to calculate sensitivity and necessary data for GA and SLP was developed in this study. Optimum design of different structures will be analyzed in numerical examples. The optimum design of structures by the improved methods of GAand SLP were proved to be better than other references in this study.
