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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/36226Full metadata record
| ???org.dspace.app.webui.jsptag.ItemTag.dcfield??? | Value | Language |
|---|---|---|
| dc.contributor.advisor | 楊烽正 | |
| dc.contributor.author | Chin-Yuan Kang | en |
| dc.contributor.author | 康志遠 | zh_TW |
| dc.date.accessioned | 2021-06-13T07:54:18Z | - |
| dc.date.available | 2007-07-28 | |
| dc.date.copyright | 2005-07-28 | |
| dc.date.issued | 2005 | |
| dc.date.submitted | 2005-07-24 | |
| dc.identifier.citation | 1 Birbil, S.I., 2002, “Stochastic Global Optimization techniques,” Department of Industrial engineering, A Dissertation Submitted to the Graduate Faculty of North Carolina State University.
2 Birbil, S.I., Shu-Cherng, F., and Ruey-Lin S., 2002, “On the Convergence of a Population-based Global Optimization Algorithm,” Kluwer Academic Publisher. 3 Birbil, S.I., and Shu-Chering, F., 2003, “An Electromagnetism-like Mechanism for Global Optimization,” Journal of Global Optimization, 25, pp. 263–282. 4 Birbil, S.I., and Orhan, F., 2003, “A Global Optimization Method for Solving Fuzzy Relation Equations,” Erasmus Research Institute of Management, Erasmus University, Department of Industrial Engineering, Galatasaray University. 5 Dieter, D., Bert, D.R., Roel, L.K., and Mario V.4, 2004, “A Hybrid Scatter Search Electromagnetism Meta-Heuristic for Project Scheduling,” European Journal of Operational Research, WORKING PAPER. 6 Fourie, P.C., and Groenwold, A.A., 2002, “The particle swarm optimization algorithm in size and shape Optimization,” Struct Multidisc Optim, 23, pp. 259–267. 7 Jacob, R., Seelig, S., and Yahya, R.S., 2002, “Particle Swarm, Genetic Algorithm, and their Hybrids: Optimization of a Profiled Corrugated Horn Antenna,” Department of Electrical Engineering University of California, Los Angeles Los Angeles, California. 8 Kennedy, J., and Eberhart, R., 1995, “Particle Swarm Optimization,” Proceedings of the 1995 IEEE International Conference on Neural Networks, IEEE Press, pp. 1942–1948. 9 Konstantinos, E.P., and Michael, N.V., 2002, “Particle Swarm Optimization Method for Constrained Optimization Problems,” Department of Mathematics, University of Patras Artificial Intelligence Research Center. 10 Parsopoulos, K.E., and Vrahatis, M.N., 2002, “Initializing the Particle Swarm Optimizer Using the Nonlinear Simplex Method,” Department of Mathematics, University of Patras University of Patras Artificial Intelligence Research Center. 11 Special session on, 2004, “Swarm Intelligence,” Congress on Evolutionary Computation, Portland, Oregon（U.S.A.）, pp. 20–23. 12 Susan, E.C., and Shonkwiler, R.,1998, “Annealing a Genetic Algorithm over Constraints,” Department of Mechanical, Aerospace and Nuclear Engineering Thornton Hall, McCormick Road University of Virginia, School of Mathematics Georgia Institute of Technology Atlanta. 13 Tao, W., 1991, “Global optimization for Constrained Nonlinear Programming,” M.E., Zhejiang University. 14 Torn, A., Ali, M.M., and Viitanen, S., 1999, “Stochastic Global Optimization: Problem Classes and Solution Techniques,” Journal of Global Optimization, 14, pp. 437–447. 15 Wang, K.P., Hung, L., and Zhou C.G., 2003, “Particle Swarm Optimization For Traveling Salesman Problem,” Proceeding of Second International Conference on Machine Learning and Cybernetics, pp. 1583–1585. 16 Xie, X., and Zhang, W., Yang, Z., 2002, “Adaptive Particle Swarm Optimization on Individual Level,” Proceedings of the 6th International Conference on Signal Processing, Beijing, China, pp. 1215–1218. 17 Yang, W.F., 2002, “A Study on the Intelligent Neural Network Training Using the Electromagnetism Algorithm,” Department of Industrial Engineering and Management, Yuan-Ze University. 18 Yang, W.F., 2002, “Textile Retail Operation using Electromagnetism Algorithm Based Neural network”, Department of Industrial Engineering and Management, Yuan-Ze University. 19 余致緯，2005，仿電磁吸斥離散優化演算法，國立台灣大學工業工程學研究所碩士論文。 20 TSPLIB標竿問題網址：http://www.iwr.uni-heidelberg.de/groups/comopt/software/TSPLIB95/index.html 21 ORLIB標竿問題網址： http://mat.gsia.cmu.edu/COLOR/instances.html | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/36226 | - |
| dc.description.abstract | 仿電磁吸斥優化演算法是新興的啟發式求解法，用以求解有界的連續實數型優化問題。本研究剖析該演算法的演算細節，分析該演算法應用於求解各類問題的共通性。提出泛用型仿電磁吸斥機制為基的優化演算法。本研究進一步探討泛用型電磁優化演算系統的設計典樣（design pattern），進行優化軟體系統功能分析和結構設計。以泛用型仿電磁吸斥優化演算法為求解核心，開發優化問題求解軟體礎架及套裝求解系統。軟體的開發均使用物件導向技術進行嚴謹的分析、規劃、設計及程式實作。本研究開發的系統包含一個核心的電磁優化軟體礎架（Framework），EMBOF；一個以MS Excel 為使用介面的電磁優化套裝軟體，EMBOS-E；一個以C# 程式語言為問題定義工具的電磁優化套裝軟體，EMBOS-NET；一個以高階API 函式呼叫的電磁優化系統開發套件，EMBOSDK。一般的使用者可以熟悉的套裝軟體模式定義問題並行求解；中階的使用者可以自己熟悉的一般程式語言定義問題；高階的使用者可以逕行使用本系統的.NET 類別庫或是經過包裝的API 函式庫，以熟悉的開發工具開發特定問題的求解系統或從事複雜問題的電磁優化技術研究。 | zh_TW |
| dc.description.abstract | The electromagnetic-like mechanism (EM) optimization algorithm is a new developing heuristic algorithm. Typical EM algorithm applies to solve continuous optimization problems without general constraints. This research analyzes the detail of EM algorithm and generalizes the compatibility of all kinds of optimization problems, and develops a meta level EM algorithm for solving all kinds of optimization problems. This research probes into the design pattern of EM and carries on systematic function analysis and structural design, then uses object-oriented technique to develop an electromagnetic attraction and repulsion simulated techniques-based optimalization software framework and applied solving systems. This research has developed four EM-based optimization system. These software systems include an MS Excel interfaced optimization package, EMBOS-E (EM-Based Optimization System for Excel); a C# programming languages interfaced software package, EMBOS-NET (EM-Based Optimization System for .NET); a software development kit for creating EM optimization solvers, EMBOSDK (EM-Based Optimization Software Development Kit); and an object-oriented software framework for optimization system developments, EMBOF (EM-Based Optimization Framework). Naive users can use EMBOS-E to setup and run their optimization problems on the Excel platform. Intermediate users can use EMBOS-NET and C# programming language to define their problems and implement additional procedures. Their written code will be runtime compiled, linked, and executed. Advanced users can either use EMBOSDK or EMBOF to develop their own solving packages. EMBOSDK uses API function calls to construct their systems. Object-oriented techniques are used to build optimization systems by using classes of EMBOF. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-13T07:54:18Z (GMT). No. of bitstreams: 1 ntu-94-R92546023-1.pdf: 3997618 bytes, checksum: 28117d938f9625e15a87204b6285a466 (MD5) Previous issue date: 2005 | en |
| dc.description.tableofcontents | 摘要 i
Abstract ii 目錄 iv 圖目錄 vi 表目錄 viii 名詞彙編 ix 符號說明 xi 第1章 緒論 1 1.1 研究背景 1 1.2 研究動機 2 1.3 研究目的及內容 3 1.4 研究範疇與架構 4 1.5 章節概要 6 第2章 文獻探討 7 2.1 求解優化問題及啟發式演算法 7 2.2 群集智慧型啟發式演算法 9 2.3 粒子群優化法演算法（PSO）之原理 10 2.4 仿電磁吸斥優化演算法（EM）之原理 15 2.4.1 仿電磁吸斥優化演算法求解應用 22 2.4 PSO和EM的分析比較 26 2.5 文獻探討結語 27 第3章 泛用型仿電磁吸斥機制為基的優化演算法 29 3.1 EM應用於求解各類優化問題 29 3.2 泛用型仿電磁優化演算流程 31 3.3 小結 42 第4章 仿電磁吸斥優化求解礎架 43 4.1 仿電磁吸斥優化礎架之系統開發動機 43 4.2 EMBOF系統模型、分析、及設計 44 4.2.1 功能模型 44 4.2.2 靜態結構模型 49 4.2.3 動態行為模型 72 4.3 EM優化求解系統的設計典樣（Design Pattern） 84 4.4 EMBOF提供的求解模組 91 4.5 目標函式值衡量機制 93 4.6 限制式處理機制 93 4.7 小結 94 第5章 EM優化系統介紹 95 5.1 Excel為介面的仿電磁優化套裝系統－EMBOS-E 95 5.2 問題程式即時編譯鏈結的仿電磁優化套裝系統－EMBOS-NET 103 5.3 仿電磁優化系統開發套件－EMBOSDK 113 第6章 結論與未來研究方向 117 6.1 結論 117 6.2 未來研究與建議 118 參考文獻 120 附件-A EMBOS-E範例演練 122 附件-B EMBOS-NET範例演練 133 | |
| dc.language.iso | zh-TW | |
| dc.subject | 仿電磁吸斥優化演算法 | zh_TW |
| dc.subject | 仿電磁吸斥優化演算法為基的求解軟體礎架及套裝求解系統 | zh_TW |
| dc.subject | 設計典樣 | zh_TW |
| dc.subject | 泛用型仿電磁吸斥優化演算法 | zh_TW |
| dc.subject | Heuristic Algorithm | en |
| dc.subject | Electromagnetism-link Mechanism | en |
| dc.subject | Framework | en |
| dc.title | 仿電磁吸斥優化演算法為基的優化問題求解系統及礎架 | zh_TW |
| dc.title | An Electromagnetic Attraction and Repulsion Simulated Techniques-based Optimalization Software Framework and Applied Solving Systems | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 93-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 黃遵鉅,胡黃德,陳正剛,林智仁 | |
| dc.subject.keyword | 仿電磁吸斥優化演算法,泛用型仿電磁吸斥優化演算法,仿電磁吸斥優化演算法為基的求解軟體礎架及套裝求解系統,設計典樣, | zh_TW |
| dc.subject.keyword | Electromagnetism-link Mechanism,Framework,Heuristic Algorithm, | en |
| dc.relation.page | 141 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2005-07-25 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 工業工程學研究所 | zh_TW |
| Appears in Collections: | 工業工程學研究所 | |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| ntu-94-1.pdf Restricted Access | 3.9 MB | Adobe PDF |
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