本論文應用蜂群演算法於結構最佳化設計中。蜂群演算法是一種模仿自然界蜜蜂覓食行為進行問題求解之方法，該法為具有群體智慧的仿生演算法，其特點為收斂速度快、參數設定少及搜尋範圍廣。蜂群演算法利用其獨特的雇用蜂以及非雇用蜂的方式進行大範圍的搜尋以尋求全域最佳解。過程中藉由食物源採用機率判斷是否採用當前最佳解，如此反覆搜尋直到找到全域最佳解為止。本研究將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，並以六種不同的範例執行結構最佳化設計。數值範例中將對各種結構做分析與討論，以結構輕量化為目的。範例中將結構最佳化問題轉為數學函數，再利用蜂群演算法對結構系統執行最佳化設計。由數值分析範例之結果，發現應用蜂群演算法於結構最佳化設計上可得到不錯的結果。 The Artificial Bee Colony (ABC) Algorithm was applied to the optimum design of structures in this study. The ABC algorithm is swarm intelligence based optimization technique inspired by the intelligent foraging behavior of honeybees. The advantage of ABC algorithm is quick convergence less settings of parameter, and extensive searching range. The employed bee and unemployed bee execute large range searching and the food source was chosen by the onlooker bee depending on the probability value associated with that food source. The FORTRAN and APDL of ANSYS software are integrated into a systematic ABC optimization program. The optimization problem can be transformed into a mathematical function. Minimum weight design will be developed in six numerical examples. Then the optimum deign of structures can be obtained by ABC algorithm. The results of ABC algorithm are better than other reference in the examples.
