摘要
讨论了传统模拟退火算法的原理、求解过程,详细地分析了它存在的局限,简单叙述了模拟退火算法中关键参数对该算法性能的影响,并给出了该算法的可行的改进方案。提出了一个改进的模拟退火算法。在该改进算法中,为避免遗失当前最优解,增加了记忆功能,将当前最好的状态记忆下来,从而使得模拟退火算法成为一种智能化算法;设计了一个自适应温度更新函数,并设置双阈值使得在尽量保持最优性的前提下减少计算量。最后用改进前后的两个算法来解决一个非线性寻找组合最优问题,实验证明改进后的模拟退火算法是高效的。
Introduced the traditional simulated annealing algorithm through discussing its theory and process, analyzed its shorteoming in detail, simply described influence of key parameters to simulated anncaling algorithm and provided feasible improvement. Then presented a method of improving simulated annealing algorithm. In order to avoid missing current optimal solution, the improved algorithm is increased memory function to remember the current best state so that it bceomes an intelligent algorithm. Also designed an adaptive temperature update function and set up dual - threshold to reduce amount of calculation. Finally, used the two algorithms to solve a no - linear problem that is searching optimization combination. Through testing, the improved simulated annealing algorithm is better than the traditional simulated annealing algorithm.
出处
《计算机技术与发展》
2009年第6期32-35,共4页
Computer Technology and Development
基金
四川省科技计划项目(2008GZ0003)
四川省科技攻关项目(07GG006-014)
中国科学院人才培养计划项目("西部之光")
关键词
模拟退火算法
马尔可夫链
最优组合
simulated annealing algorithm
Markov chain
optimization combination
