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研究生:洪國強
研究生(外文):Hong Kuoch'iang
論文名稱:粒子群集法於圓形物件排列的應用
論文名稱(外文):The Application of Particle Swarm Optimization Method in Round Chip Allocation
指導教授:紀華偉
指導教授(外文):Ji Huawei
學位類別:碩士
校院名稱:大葉大學
系所名稱:機械工程研究所碩士班
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:中文
論文頁數:71
中文關鍵詞:粒子群集法圓形物件排列演算法穩定性群集法權重範圍
外文關鍵詞:PSOdesignsystem
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粒子群最佳化演算法(Particle Swarm Optimization, PSO)是由Eberhart和Kennedy兩位博士所提出的演算法。PSO源起對於鳥群捕食行為的觀察過程,由簡單的個體組合而成的群體以及個體之間的互動行為,透過科學模擬系統從局部信息來產生不可預測的群體行為,藉以有效達到覓食的目標,同時來簡化說明社會生命現象,避免採取隱喻機制的演算法來解決問題。
本論文利用PSO演算法,以族群為基礎於設計空間中,進行搜尋運算的特性排列物件,探討PSO更新機制對於排列的影響。在結果中得知,速度慣性權重(inertia weighted)對於粒子移動的穩定性有關,加速度常數(acceleration constant)的大小影響收斂速度的快慢。對於排列的結果,速度慣性權重與加速度常數影響較不明顯,影響較明顯的則是初始產生的位置範圍。
Dr. Eberhart and Dr. Kennedy propose induction, Particle Swarm Optimization, PSO, which origins from the birds capturing the food such this process which combines of simple individual. The interaction combines with individual and group. Through the scientific imitate system coming from the message of some parts to produce the unpredictable the behaviors which combine lots of groups, in order to hunt for the food; meanwhile, it can simplify to state the phenomenon of social life circle, in order to avoid the induction of metaphor to solve the problem.
The purpose of the thesis is to use the group, PSO as the basis which can search for the operation in the design space. It can try to use the PSO searching for the order of Optimization, in order to discuss the best way. From the outcome, inertia weighted is related to the stability of the moving particle. The affect of the size to acceleration constant is related to the speed of velocity. From the outcome of its arrangement, it is unclear to the affect of the inertia weighted and the acceleration constant. The most obvious affect is its scope of the beginning production.
封面內頁
簽名頁
授權書..............................................iii
中文摘要.............................................v
英文摘要.............................................vi
誌謝.................................................vii
目錄.................................................viii
圖目錄...............................................x
表目錄...............................................xii

第一章 緒論...........................................1
1.1 前言 ............................................1
1.2 研究目的與內容....................................2
1.3 研究方法與架構....................................2
第二章 文獻探討.......................................4
第三章粒子群演算......................................11
3.1 粒子群最佳化演算法簡介.............................11
3.2 粒子群最佳化演算法運算方式.........................12
3.3 PSO運算流程與演算法流程圖.........................15
第四章 問題描述與範例.................................18
4.1 問題之定義......................................18
4.2物件排列方程式...................................18
4.3結果與討論......................................20
4.4.1粒子數........................................23
4.4.2菁英再啟動....................................28
4.4.3速度慣性權重..................................30
4.4.4最佳位置權重係數..............................34
4.4.5初始排列邊界..................................34
第五章 結論與未來展望...............................42
5.1 結論..........................................42
5.1 未來展望.......................................42
參考文獻.........................................44
附錄.............................................48
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[14].Clerc, M., and Kennedy, J. (2000) ,”The particle swarm: Explosion, stability, and convergence in a multimodal complex space,”Proceedings of the Congress of Evolutionary Computation, Vol. 6, 58-73, Washington DC, IEEE, Piscataway, NJ, USA.
[15].Eberhart, R.C. and Shi, Y. (2000) ,”Comparing inertia weights and constriction factors in particle swarm optimization,”Proceeding of the 2000 Congress of Evolutionary Computation, Vol 1, 84-88, California, CA, USA, IEEE, Piscataway, NJ, USA.
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