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| 基于模拟退火的进化算法性能对比研究 | |
| 引用本文： | 汪灵枝,申锦标,赵世安. 基于模拟退火的进化算法性能对比研究[J]. 百色学院学报, 2007, 20(3): 43-47 |
| 作者姓名： | 汪灵枝 申锦标 赵世安 |
| 作者单位： | 1. 柳州师范高等专科学校,数学与计算机科学系,广西柳州,545004 2. 广西大学,数学与信息科学学院,广西南宁,530004 3. 百色学院,数学与计算机科学系,广西百色,533000 |
| 摘 要： | 将模拟退火算法和遗传算法、粒子群优化算法分别进行结合,形成模拟退火—遗传算法以及模拟退火—粒子群优化算法,并作性能对比分析。研究结果表明,这两种算法都在进化代数和全局寻优能力方面有较大突破,在找寻最佳个体解的效率上,模拟退火—粒子群优化算法更突出。 |
| 关 键 词： | 模拟退火 遗传算法 粒子群优化算法 |
| 文章编号： | 1673-8233（2007）03-0043-05 |
| 修稿时间： | 2007-03-12 |
On Evolution Algorithm Ability Based on Simulated Annealing |
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| WANG Ling-zhi,SHEN Jin-biao,ZHAO Shi-an. On Evolution Algorithm Ability Based on Simulated Annealing[J]. , 2007, 20(3): 43-47 | |
| Authors: | WANG Ling-zhi SHEN Jin-biao ZHAO Shi-an |
| Affiliation: | 1. Department of Mathematics and Computer Science, Liuzhou Teachers College, Liuzhou 545004, China; 2. College of Mathematics and Computer Science, Guangx University, Nanning 530004, China; 3. Department of Mathematics and Computer Science, Baise University, Baise 533000, China |
| Abstract: | This paper presents the respectively combining of simulation annealing with genetic algorithms and particle swarm optimization,forming SA-GA and SA-PSO algorithms,and compares and analyzes their ability.The results show that the two algorithms,compared with SA-PSO algorithm,have a greater breakthrough in evolution algebra and overall situation optimization ability,and they are better in seeking for the most precise individual result. |
| Keywords: | Simulation Annealing Genetic Algorithm Particle Swarm Optimization |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |