运城学院学报
運城學院學報
운성학원학보
JOURNAL OF YUNCHENG UNIVERSITY
2011年
5期
8-12
,共5页
云模型%人口迁移算法%函数优化
雲模型%人口遷移算法%函數優化
운모형%인구천이산법%함수우화
cloud model%population migration algorithm%function optimization
针对人口迁移算法搜索速度较慢，易陷入局部最优的缺点，改进了算法思想，简化了算法步骤，并利用云模型云滴的随机性和稳定倾向性的特点，由基本云发生器实现人口流动操作，提出了一种云人口迁移算法，用于求解具有变量边界约束的非线性的复杂函数最优化问题。实验仿真结果表明，云人口迁移算法具有计算精度较高，搜索速度较快等特点。
針對人口遷移算法搜索速度較慢，易陷入跼部最優的缺點，改進瞭算法思想，簡化瞭算法步驟，併利用雲模型雲滴的隨機性和穩定傾嚮性的特點，由基本雲髮生器實現人口流動操作，提齣瞭一種雲人口遷移算法，用于求解具有變量邊界約束的非線性的複雜函數最優化問題。實驗倣真結果錶明，雲人口遷移算法具有計算精度較高，搜索速度較快等特點。
침대인구천이산법수색속도교만，역함입국부최우적결점，개진료산법사상，간화료산법보취，병이용운모형운적적수궤성화은정경향성적특점，유기본운발생기실현인구류동조작，제출료일충운인구천이산법，용우구해구유변량변계약속적비선성적복잡함수최우화문제。실험방진결과표명，운인구천이산법구유계산정도교고，수색속도교쾌등특점。
Population migration algorithm （PMA） easily gets stuck at a local optimum, and often has slow convergent speed. A novel population migration algorithm, cloud -model -based population migration algorithm （CPMA） is proposed. CPMA used for optimizing complex nonlinear function is based on both the idea of improved population flow and the properties of randomness and stable tendency of a normal cloud model. A basic normal cloud generator is used as the population flow operator and its algorithm step is simplified. Finally, the numerical experiment results show that this method not only can effectively locate the global optimum, but also have a rather high convergence speed.
