| 引用本文: | 李守智,李敏远,潘永湘.遗传退火算法及收敛性分析（英文）[J].控制理论与应用,2002,19(3):376~380.[点击复制] |
| LI Shouzhi, and,LI Minyuan,PAN Yongxiang.Genetic Annealing Algorithm and Its Convergence Analysis[J].Control Theory and Technology,2002,19(3):376~380.[点击复制] |
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| 遗传退火算法及收敛性分析（英文） |
| Genetic Annealing Algorithm and Its Convergence Analysis |
| 摘要点击 3997 全文点击 1268 投稿时间：2000-06-08 修订日期：2001-04-23 |
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| DOI编号 10.7641/j.issn.1000-8152.2002.3.011 |
| 2002,19(3):376-380 |
| 中文关键词 全局优化 遗传退火算法 收敛性 |
| 英文关键词 global optimization genetic annealing algorithm convergence |
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| 中文摘要 |
| 针对模拟退火算法收敛速度慢和遗传算法存在种群退化问题, 将二者有机地结合在一起, 提出了遗传退火算法, 证明了该算法的收敛性. 仿真结果表明, 遗传退火算法既克服了模拟退火算法收敛速度慢, 又解决了遗传算法中种群退化问题. 该算法不仅适用于一般的组合优化问题, 也适用于目标函数不确定和可变的情况. |
| 英文摘要 |
| Aiming at low convergence speed of simulated annealing algorithm and group degeneration in genetic algorithm, we present a genetic annealing algorithm that combines the above two ones and also prove its convergence. Simulation results illustrate that genetic annealing algorithm not only overcomes the low convergence speed in simulated annealing algorithm but also solves the group degeneration problem in genetic algorithm. This algorithm can be used to solve the problem with uncertain and variant objective function as well as general combined optimization problem. |
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