本論文主要目的在設計最佳化的引擎吊架，引擎吊架主要的組成構件包括吊臂桿、吊架主體、油壓缸及兩根輔助桿，設計目標為輕量化引擎吊架的總重量，最佳化設計的設計變數為各管件截面尺寸、支撐點位置及吊架主體的角度等，除此我們也將管件截面尺寸、系統參數及負載重量視為隨機變數，採用可靠度拘束條件進行最佳化設計，文中利用基因演算法來搜尋目標函數的最佳解，搜尋方式不僅使用連續式搜尋法，也使用離散式搜尋法，以材料規格表中給定的尺寸作搜尋，最佳化結果顯示，隨機變數之變異值愈大或可靠度要求值愈高，則最佳設計的總重量就會隨之增加，雖然採用離散式搜尋法所得到的重量會比連續式搜尋法來得重些，但其結果更具實用價值。

This thesis aims at designing an optimal engine hoist which mainly consists of a lifting boom, a body of hoist, a hydraulic jack, and two auxiliary arms. The design object is to minimize the weight of engine hoist. The design variables include the cross-section size of tubes, the position of support, and the supporting angle of body of hoist etc. In addition we regard cross-section size of tubes, system parameters, and loading weight as random variables. Performing the optimization by using the reliability constrained conditions. The genetic algorithm is used to solve the optimal solutions and there are two different ways to search for the answer; continuous search and discrete search. In discrete search, set a particular range for the parameters in the specification of materials and make a search from it. The outcomes of the optimization show that the total weights will increase when the variation and required reliability are high. Although the total weights which by using the discrete search will heavier than by using continuous search, the former one is worth.

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