臺灣博碩士論文加值系統

回顧從1995年以來的開發過程,微粒優化法（Particle Swarm Optimization, PSO）由Kennedy 教授和Eberhart教授提出，並成功解決了許多優化上的問題。

PSO演算法是一種智慧型計算技術，其優點是收斂速度快且參數設定較少。

本文為了進一步提高算法效率，提出一種改良的PSO演算法，是在基本PSO算法基礎上引入了遺傳算法的突變機制。

由於PSO參數一直沒有個固定設法，所以本文研究了不同參數選擇對演算法的影響，把優化問題分為三類(簡易、中等、困難)，本文提出的改良微粒演算法分別處理三類優化問題。

然后根據測試结果對其參數設置進行系统性分析。

Developments in the Particle Swarm Optimization(PSO) since 1995 are reviewed. The proposal of Particle Swarm Optimization by professor Kennedy and Eberhart has been succeeded in solving for many optimization problems.

Particle Swarm Optimization algorithm is a new soft computation method. which has the features of rapid convergence speed and fewer parameters needed to be adjusted.

In this paper, to improve the calculation efficiency, the modified Proposes one kind of improvement pso algorithm is based on basic PSO algorithm ,and the mutation of genetic algorithm is introduced.

Due to the undetermined parameters in PSO，and the extensive analysis on the effect of different parameters on the algorithm is given. Classifying optimization problems into three classes (easy,medium,difficult), this paper suggests an improved algorithm of PSO to handle three classes of optimization problems respectively.

Then, parameter settings are analyzed systematically according to some existed testing results.

封面內頁
簽名頁
授權書．．．．．．．．．．．．．．．．．．．．．．．．． iii
中文摘要．．．．．．．．．．．．．．．．．．．．．．．． iv
英文摘要．．．．．．．．．．．．．．．．．．．．．．．． v
誌謝．．．．．．．．．．．．．．．．．．．．．．．．．． vi
目錄．．．．．．．．．．．．．．．．．．．．．．．．．． vii
圖目錄．．．．．．．．．．．．．．．．．．．．．．．．． ix
表目錄．．．．．．．．．．．．．．．．．．．．．．．．． x

第一章　緒論
1.1簡介．．．．．．．．．．．．．．．．．．．． 1
1.2論文探討．．．．．．．．．．．．．．．．．． 2
1.3論文大綱．．．．．．．．．．．．．．．．．． 3
第二章　微粒優化法理論
2.1微粒優化法(PSO)理論．．．．．．．．．．．．．．．．4
2.2 PSO應用情況．．．．．．．．．．．．．．．．．．．．11
2.3 PSO優點與缺點檢討．．．．．．．．．．．．．．．．13
第三章 一般PSO改良法介紹
3.1 PSO演算法對 設限．．．．．．．．．．．． 16
3.1.1 PSO演算法對 設限的原理介紹．．．．16
3.2 線性遞減權重．．．．．．．．．．．．．．．． 17
3.2.1線性遞減權重的原理介紹．．．．．．．．17
3.2.2線性遞減權重的運算步驟．．．．．．．．18
3.3收縮因子k ．．．．．．．．．．．．．．．．18
3.3.1收縮因子k的原理介紹．．．．．．．．．19
3.3.2收縮因子k的運算步驟．．．．．．．．．20
3.4 擇優．．．．．．．．．．．．．．．．．．．．21
3.4.1收縮因子k的原理介紹．．．．．．．．．21
第四章 範例分析
4.1難度分析．．．．．．．．．．．．．．．．．．．．．． 24
4.1.1難度1：Rastrigin function．．．．．．．．．．． 24
4.1.2難度1：Sphere function．．．．．．．．．．．．25
4.1.3難度2：Rosenbrock function．．．．．．．．．26
4.1.4難度3：Schaffer function．．．．．．．．．．．28
第五章 改良式PSO方法提出
5.1突變改良法．．．．．．．．．．．．．．．．．．．．． 31
5.2加入突變的微粒優化法(難度容易)．．．．．．．．．33
5.3加入突變的微粒優化法(難度中等)．．．．．．．．． 35
5.1加入突變的微粒優化法(難度困難)．．．．．．．35
第六章 模擬測試
6.1模擬結果．．．．．．．．．．．．．．．．．．37
第七章 結論．．．．．．．．．．．．．．．．．．．．．． 53
參考文獻．．．．．．．．．．．．．．．．．．．．．．．． 57
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