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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/11518

Title: 遺傳演算法於船體結構多目標最佳化設計之應用
Genetic Algorithms for Multi-objective Optimization of Ship Structures
Authors: 郭信川
Contributors: NTOU:Department of Systems Engineering and Naval Architecture
國立臺灣海洋大學:系統工程暨造船學系
Keywords: 遺傳演算法;多負荷狀況;船舶結構多目標;最佳化設計
genetic algorithms;multiple load cases;multi-objective optimization of ship structures
Date: 2000
Issue Date: 2011-06-28T08:20:05Z
Publisher: 行政院國家科學委員會
Abstract: 遺傳演算法產生新族群的控制參數有交配、突變、交配點、懲罰因子以及保留最佳個體策略等。本文首先針對這些參數於多極值與非凸區域最佳化問題之全域最佳解進行一系列測試,並對其搜尋結果討論,嘗試提出對搜尋全域最佳解且高成功率的較適當的參數狀況。藉此,檢討多負荷狀況下結構最佳化設計的處理方式,提出一個較具經濟效益與搜尋到符合安全的合理狀況,最後於船舶結構多目標最佳化設計以最大最小法和線性權重和法處理並討論。
The parameters in a genetic algorithm generating new population are crossover 、 mutation 、 crossoverpoin t、penalty factor and elitist strategy. First, in this thesis, the searching properties for those parameters on the global optimum for multi-mode functions and non-convex domain optimization problems are studied by a series tests. From the searching results, the better way using parameters for the genetic algorithm searching the global optimum with a better performance could be found. With these genetic algorithms, the optimization of ship's structures under multiple load cases is carried out. Two approaches used for the optimization problems, the results are discussed and an efficient approach finding a rational safety solution is suggested, also. Finally, with the genetic algorithm, the max-min method and linear weighting sum method are used to study the multi-objective optimization of ship structural optimizations serve as the illustrative examples.
Relation: NSC89-2611-E019-041
URI: http://ntour.ntou.edu.tw/ir/handle/987654321/11518
Appears in Collections:[系統工程暨造船學系] 研究計畫

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