[1]任斌,丰镇平.改进遗传算法与粒子群优化算法及其对比分析[J].南京师范大学学报(工程技术版),2002,02(02):014-20.
 Ren Bin,Feng Zhenping.Improved Genetic Algorithm and Particle Swarm Optimization as well as Comparison between Them[J].Journal of Nanjing Normal University(Engineering and Technology),2002,02(02):014-20.
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改进遗传算法与粒子群优化算法及其对比分析
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南京师范大学学报(工程技术版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
02卷
期数:
2002年02期
页码:
014-20
栏目:
出版日期:
2002-06-30

文章信息/Info

Title:
Improved Genetic Algorithm and Particle Swarm Optimization as well as Comparison between Them
作者:
任斌丰镇平
西安交通大学叶轮机械研究所, 710049, 西安
Author(s):
Ren Bin Feng Zhenping
Institute of Turbomachinery, Xian Jiaotong University,710049,Xian,PRC
关键词:
函数优化 改进遗传算法 粒子群优化算法
Keywords:
function optimization improved genetic algorithm par ticle swarm optimization
分类号:
TP18
摘要:
进化算法作为一类新的优化搜索方法 ,广泛应用于各种优化问题 .现对简单遗传算法进行了改进 ,采用实值编码 ,并与模拟退火算法及基于适值排序和随机选择的方法相结合 ,形成了改进遗传算法 .同时还介绍了一种新的进化算法—粒子群优化算法 .将这两种优化算法应用于函数优化 ,并对优化结果进行了对比分析 .比较结果表明 ,改进遗传算法和粒子群优化算法都可以在函数优化方面表现出较好的健壮性 ,但在找寻最优解的效率上 ,粒子群优化算法较好 .
Abstract:
As a new kind of optimization search techniques, the evolut ionary algorithms are widely used to solv e differ ent pr oblems in optimal areas. After a careful research, t he simple genetic algor ithm has been impr oved by adopting float- coding method, simulated annealing algor ithm and sor ted stochastic fitness selection strategy; and has been applied to mathematic function optimization. In addition, a new evolutionar y algorit hm- Particle Sw arm Optimization is intro duced and applied to the same mathematic function opt imization. The optimization r esults ar e compared with each other in this paper. The compar at ive result indicates that the Improved Genetic Algor ithm and Particle Sw arm Optimizatio n are both robust. But Par ticle Swarm Opt imization can obtain the optimum solut ions more easily than the Improved Genetic Algor ithm, and it is a good optimization method w ith strong competitiveness.

参考文献/References:

[ 1] 任平. 遗传算法( 综述) [ J] . 工程数学学报, 1999, 16( 1) : 1~ 8.
[ 2] 丰镇平, 李军, 沈祖达. 遗传算法及其在透平机械化设计中的应用[ J] . 燃气轮机技术, 1997, 11( 2) : 13~ 22.
[ 3] Li Jun, Feng Zhenping, et al . Aerody namic Optimum Design of Transonic Turbine Cascades Using Genet ic Algo rithms[ J] .Journal of T hermal Science, 1997, 6( 2) : 364~ 368.
[ 4] 童彤, 丰镇平, 李军. 遗传算法在透平叶栅多目标优化设计中的应用[ J] . 中国电机工程学报, 1999, 19( 6) : 74~ 76.
[ 5] V. Tandon. NC End Milling Opimization Using Evo lutionary Computation[ J] . International Journal of Machine Tools and Manufacture, 2001, 42: 595~ 605.
[ 6] 王雪梅, 王义和. 模拟退火算法和遗传算法的结合[ J] . 计算机学报, 1997, 20( 4) : 381~ 384.
[ 7] F Zhang, D Xue. Optimal Concur rent Design Based upon Distributed Product Development Life- cycle Modeling[ J] . Robo tics and Computer Integ rated Manufacturing, 2001, 17: 469~ 486.
[ 8] A R Cockshott, B E Har tman. Improving the Fermentation Medium for Echinocandin B Productio n Part Ⅱ : Particle Sw arm Opt imization[ J] . Process Biochemistry, 2001, 36: 661~ 669.
[ 9] [ 美] Z. 米凯利维茨, 著. 演化程序——遗传算法和数据编码的结合[M] . 周家驹, 等译. 北京: 科学出版社, 2000, 103.

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备注/Memo

备注/Memo:
基金项目: 教育部高校骨干教师资助计划资助( GG- 807-10698- 1016)
作者简介: 任斌, 1974- , 西安交通大学叶轮机械研究所博士研究生, 从事叶轮机械气动热力学优化研究
更新日期/Last Update: 2013-04-29