遗传模拟退火算法——黑龙江TSP问题
发布时间:2018-10-29 11:48
【摘要】:以黑龙江省29个城市构造TSP问题,通过对实验数据的分析,得出了遗传模拟退火算法在求解精度上优于遗传算法或模拟退火算法。遗传模拟退火算法利用了模拟退火算法局部精确的求解能力补充了遗传算法在局部求解不够精确的弊端,从而加快了求解TSP问题的效率,同时,又将蚁群算法和遗传模拟退火算法做比较,从结果可以看出遗传模拟退火算法求解效果较好。
[Abstract]:The TSP problem is constructed in 29 cities of Heilongjiang Province. Through the analysis of the experimental data, it is concluded that the genetic simulated annealing algorithm is superior to the genetic algorithm or simulated annealing algorithm in solving the problem. Genetic simulated annealing algorithm makes use of the local accurate solving ability of simulated annealing algorithm to supplement the disadvantage of genetic algorithm which is not accurate in local solution, thus speeding up the efficiency of solving TSP problem, at the same time, By comparing ant colony algorithm with genetic simulated annealing algorithm, it can be seen that genetic simulated annealing algorithm is effective.
【作者单位】: 黑龙江科技大学理学院;
【分类号】:O1-0
本文编号:2297601
[Abstract]:The TSP problem is constructed in 29 cities of Heilongjiang Province. Through the analysis of the experimental data, it is concluded that the genetic simulated annealing algorithm is superior to the genetic algorithm or simulated annealing algorithm in solving the problem. Genetic simulated annealing algorithm makes use of the local accurate solving ability of simulated annealing algorithm to supplement the disadvantage of genetic algorithm which is not accurate in local solution, thus speeding up the efficiency of solving TSP problem, at the same time, By comparing ant colony algorithm with genetic simulated annealing algorithm, it can be seen that genetic simulated annealing algorithm is effective.
【作者单位】: 黑龙江科技大学理学院;
【分类号】:O1-0
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