算法引入模拟退火机制，在遗传进化过程中的每一代，对最优个体进行邻域局部寻优，利用模拟退火进一步改善算法的收敛性能。

Simulated annealing mechanism is introduced to do local-search for the best chromosome in every generation of the evolution process. This improves the convergence of the algorithm.

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用其他随机优化算法（模拟退火算法、遗传算法、进化规划等）与免疫算法进行了比较研究，给出了他们的异同点、免疫算法的优点等。

We made improvement to the search mechanism of the traditional Ant Colony Algorithm(ACA), put forward a Random Ant Colony Algorithm(RACA), and applied it in air combat decision.

youdao

用其他随机优化算法（模拟退火算法、遗传算法、进化规划等）与免疫算法进行了比较研究，给出了他们的异同点、免疫算法的优点等。

We made improvement to the search mechanism of the traditional Ant Colony Algorithm(ACA), put forward a Random Ant Colony Algorithm(RACA), and applied it in air combat decision.

youdao