|
|||||
|
|
| 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]. 广西右江民族师专学报, 2007, 0(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 |
| 基金项目： | 基金项目：广西教育厅资助项目（200508234）. |
| 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士，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 |
On Evolution Algorithm Ability Based on Simulated Annealing |
|
| Affiliation: | WANG Ling-zhi , SHEN Jin-biao, ZHAO Shi-an (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 corn-pares 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 abili-ty, 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 维普 等数据库收录！ | |