本研究參考修正螢火蟲演算法與結合近鄰吸引之螢火蟲演算法此兩種啟發式演算法，提出結合近鄰吸引之修正螢火蟲演算法，使用十一種最佳化測試函數為範例，比較布穀鳥搜尋演算法、螢火蟲演算法、修正螢火蟲演算法、結合近鄰吸引之螢火蟲演算法、結合近鄰吸引之修正螢火蟲演算法等五種演算法的最佳化結果，歸納新演算法的優勢特性，並將其運用於引擎腳的幾何最佳化。藉由對橡膠材料進行拉伸及鬆弛試驗，並進行實驗數據曲線的擬合結合有限元素法的使用，可以得到適用於引擎腳的橡膠材料之材料模型參數。研究中使用啟發式演算法結合有限元素分析軟體Ansys，分別以靜態剛性幾何最佳化、動態剛性幾何最佳化及同時考慮動態與靜態剛性之幾何最佳化共三種最佳化目標進行引擎腳的外型設計，其中以靜態剛性幾何最佳化確認求得具平滑外型設計之引擎腳所需的設計參數數量；以動態剛性幾何最佳化確認適用於本研究中設定之邊界條件與設計區間的動態剛性目標。最後於同時考慮動態與靜態剛性之幾何最佳化中調整動態與靜態剛性於目標函數中所占的權重比，以求得同時符合動態與靜態剛性設計規格之引擎腳設計。

This study combines the modified firefly algorithm and firefly algorithm with neighborhood attraction to form a new modified algorithm called modified firefly algorithm with neighborhood attraction. Eleven functions are used for testing optimization algorithms. The results from the proposed algorithm are compared with the results from cuckoo search, firefly algorithm, modified firefly algorithm, and firefly algorithm with neighborhood attraction. The results show that the modified firefly algorithm with neighborhood attraction has better computational efficiency. In this study, a geometry optimization method for design of rubber mounts is developed which combines the heuristic algorithm and commercial finite element analysis program, Ansys. A nonlinear finite element model is created in Ansys software to estimate the stiffness values of the rubber mounts. The curve fitting process is used to obtain both hyperelastic and viscoelastic material parameters of rubber after tensile and relaxation tests. Three optimization cases including static stiffness optimization, dynamic stiffness optimization, and both static and dynamic stiffness optimization have been considered in this research. The designs of rubber mounts to achieve the target values of both the static and dynamic stiffness are presented.

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