陕西科技大学学报(自然科学版)
陝西科技大學學報(自然科學版)
협서과기대학학보(자연과학판)
JOURNAL OF SHAANXI UNIVERSITY OF SCIENCE & TECHNOLOGY
2010年
2期
17-23
,共7页
粒子群优化%tent映射%Logistic映射%均匀性%最大聚集距离%高斯变异%稳定性
粒子群優化%tent映射%Logistic映射%均勻性%最大聚集距離%高斯變異%穩定性
입자군우화%tent영사%Logistic영사%균균성%최대취집거리%고사변이%은정성
PSO%tent map%logistic map%uniformity%maximal focus distance(maxdist)%gaussian mutation%stability
粒子群优化算法是一种基于群体智能的随机优化算法,针对粒子群优化算法稳定性较差和易陷入局部收敛的缺点,作者提出了一种基于tent映射和logistic映射的粒子群算法,一方面,分别应用tent映射和logistic映射初始化均匀分布的粒群提高了初始解的质量;另一方面,设定粒子聚集程度的量化计算公式和判定阈值,并引入自适应高斯变异策略,增强了算法跳出局部最优解的能力.通过对基准测试函数的仿真计算,证明该算法具有稳定性好和收敛速度快的特点.
粒子群優化算法是一種基于群體智能的隨機優化算法,針對粒子群優化算法穩定性較差和易陷入跼部收斂的缺點,作者提齣瞭一種基于tent映射和logistic映射的粒子群算法,一方麵,分彆應用tent映射和logistic映射初始化均勻分佈的粒群提高瞭初始解的質量;另一方麵,設定粒子聚集程度的量化計算公式和判定閾值,併引入自適應高斯變異策略,增彊瞭算法跳齣跼部最優解的能力.通過對基準測試函數的倣真計算,證明該算法具有穩定性好和收斂速度快的特點.
입자군우화산법시일충기우군체지능적수궤우화산법,침대입자군우화산법은정성교차화역함입국부수렴적결점,작자제출료일충기우tent영사화logistic영사적입자군산법,일방면,분별응용tent영사화logistic영사초시화균균분포적립군제고료초시해적질량;령일방면,설정입자취집정도적양화계산공식화판정역치,병인입자괄응고사변이책략,증강료산법도출국부최우해적능력.통과대기준측시함수적방진계산,증명해산법구유은정성호화수렴속도쾌적특점.
Particle swarm optimization(PSO) is a population-based stochastic optimization originating from artificial life and evolutionary computation.PSO, however, has a feature of un-stability during its running, and like other evolutionary algorithms, has a tendency to get stuck in local optimal solutions during the search process. So, two improved particle swarm optimization are proposed in this paper, which are PSO with an initial population of tent map solutions and Gaussian mutation based on maximal focus distance(Tent-PSO) and PSO with an initial population of logistic map solutions and Gaussian mutation based on maximal focus distance(Logistic-PSO), respectively. Simulation results on two benchmark functions illustrate that the PSO proposed in this paper is feasible and efficient.
