摘要
提出了一种基于局部搜索机制快速求解TSP的遗传算法。基于局部搜索机制,自适应地将标准遗传算法与局部启发式算法结合,使得局部启发式算法只在有效改善种群个体质量的情况下才允许执行,有效地避免了因局部搜索次数过多而引起的陷入局部最优和计算负担过重现象的发生。仿真结果表明,该算法具有较强的全局优化能力及较快的收敛速度,在求解TSP问题时有较高效率。
This paper proposes a genetic algorithm based on local search mechanism quickly solving TSP.Based on local search mechanism,this paper adaptively combines standard genetic algorithm with local heuristic algorithm,so that local heuristic algorithm is allowed to execute only when individual quality is effectively improved,and thus avoid effectively phenomena of local optimum or computational overburden due to excessive number of local search.Simulation results show that this algorithm has a strong global optimization ability,fast convergence speed,and high efficiency in solving TSP.
出处
《浙江理工大学学报（自然科学版）》
2014年第3期287-291,共5页
Journal of Zhejiang Sci-Tech University(Natural Sciences)
基金
国家自然科学基金(61374022)
国家高新技术研究发展项目(2009AA04Z139)
关键词
局部搜索机制
自适应
遗传算法
旅行商问题
local search mechanism
adaptive
genetic algorithm
traveling salesman problem
