本文主要為發展適用於免疫演算法的限制條件處理策略。免疫演算法的原理是模仿B細胞表面受體上的Y型重鏈及輕鏈基因結構，藉由基因的高度突變完成病原體的解碼，達到最佳化的求解。處理限制的轉換目標策略是將限制條件的違反量轉換為另一目標函數，將此另一目標函數與原目標函數進行非支配排序，可得到Pareto前沿解，當另一個函數值為0的點即表示符合所有的限制條件。本文以發展完成的限制免疫最佳化演算法(CIA)，進一步發展處理含限制的雙目標最佳化問題及含限制的多極值最佳化問題。並以多個數值例題呈現及檢驗解題的精確性及演算法的穩健性及效率。
含限制的免疫最佳化應用於電熱微致動器的最佳化工程設計，應用到有限元素軟體(ANSYS)與免疫最佳化演算連結，設計微致動器的結構及輸入電壓以達到最大的位移效果。另一個設計問題是含三種材料的震動台，最小化成本達到最大震動效果的雙目標最佳化設計，應用到ANSYS與免疫演算法做連結，結果為多組解可供設計者選擇。含限制的多極值免疫最佳化程序，被應用於桁架拓樸設計與分析，本文採用了二階段設計程序。第一階段為排列桁架可能的型態，再經第二次型態與結構尺寸同步設計程序，最後可得到多種型態的設計結果，每種排列結構相當於不同尺寸的區域最佳解。其中包含平面及空間桁架結構設計，結果與參考文獻結構相同或較佳。 The presenting thesis mainly proposes a constraints handling strategy applied for immune system algorithm (IA). The theory of such an IA simulates the gene structures of Y-shape heavy chain and light chain on B-cell receptor. The key decoded operator is somatic mutation where the gene evolves to the final optimum. In dealing with constraints, an objective transform strategy is proposed where all violations are organized to an additional objective function. Then, the non-dominate method is utilized for two objective function problem. The final optimum converge at when the additional objective function evolving to zero. This constraints handling technique is further applied and adapted to double-objective constrained optimization problem. The other application of the proposed constraints handling is applied to the multimodal constrained problems.
The engineering designs presented in the thesis include single-arm and two-arm micro electromechanical actuators design and analysis. The I-beam and vibrating platform structural design contain two-objective functions and constraints. The result shows that the proposed method is reliable and efficient. Several constrained topological truss design are illustrated by presented constrained multimodal algorithm. The better performances can be obtained as compared published papers.
