摘要
自从Adleman博士利用分子算法成功求解HPP问题,DNA计算引起了人们广泛的兴趣.文中引入了DNA技术并借助生物学理论对其进行改进,提出了新的分子优化算法.并在机器人路径的避障规划中进行了仿真实例,结果显示算法避免了经典遗传算法容易出现的“早熟收敛”和“收敛速度慢”两大难题,继承了遗传算法全局搜索的能力,提高了算法的有效性和收敛速度,在很少的进化代数中就可以求得问题的最优解,适合于路径规划问题.
Interest in DNA computing has increased overwhelmingly since Adleman successfully demonstrated its capability to solve Hamiltonian Path Problem. This article introduces the improving method in virtue of the biological thery of DNA technology, a new molecular algorithm is advanced. After a numerical simulation, the result shows that it avoids the prematurely and lower convergent speed of the classic genetic algorithm, and inherits global search capability, the validity and the speed of the genetic algorithm have been increased. The best result can be obtained in few iterative times. It is fit for solving path planning problem.
出处
《重庆大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2007年第1期102-105,共4页
Journal of Chongqing University
基金
国家"十五"重庆科技攻关资助项目(2002BA107B04-2)
国家自然科学基金资助项目(10671132)
关键词
DNA计算
遗传算法
路径规划
DNA computation
genetic algorithm
path planning
