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提出了一种蚁群算法与遗传算法相混合的算法。将遗传算法加入到蚁群算法的每一次迭代的过程中,利用遗传算法全局快速收敛的特点,来加快蚁群算法的收敛速度。并且遗传算法中的变异机制,帮助提高了蚁群算法取不到局部最优解的能力。不仅阐述了新算法的原理,而且以TSP问题的求解为例进行了相关的实验,实验结果表明新算法即蚁群遗传混合算法(ACGA)在求解时间和求解质量上都取得了很好的效果。
A hybrid algorithm of ant colony algorithm and genetic algorithm is proposed. The genetic algorithm is added to each iteration of the ant colony algorithm, and the convergence speed of the ant colony algorithm is accelerated by utilizing the characteristics of global convergence of genetic algorithm. And the mutation mechanism in genetic algorithm helps to improve the ability of ant colony algorithm to get the local optimal solution. Not only the principle of the new algorithm is explained, but also the relevant experiments are carried out by taking the solution of TSP as an example. The experimental results show that the new algorithm, ACGA, achieves good results both in solving time and solving quality .