仿電磁吸斥優化演算法為基的優化問題求解系統及礎架

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。

關鍵字

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

並列摘要

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.

並列關鍵字

Electromagnetism-link Mechanism ； Framework ； Heuristic Algorithm

參考文獻

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.

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.

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.

國際替代計量

仿電磁吸斥優化演算法為基的優化問題求解系統及礎架

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