冒泡择优遗传算法

为快速地寻求复杂多峰函数的全局极值点，提出一种冒泡择优遗传算法。它以冒泡的形式让每一代种群中的最优的个体参加列队竞争，以成为局部最优或全局最优。对于达到局部极值的个体，进行湮灭操作，重新进行进化与列队竞争。该算法能自动保持种群多样性且易于实现。实验结果表明，该算法对于求解多峰函数优化的问题十分有效，通常都能找到全部全局最优解。

Genetic Algorithms for Bubbling and Selecting the Best

To search all optimal solutions(global minimum), this paper brings forward a bubbling and selecting the best genetic algorithm.It selects the best individual of population of every generation to join local searching.It means that the individual may be the local minimum or the global minimum.The individual as the local minimum should be annihilated and join evolution and local searching. The algorithm can automatically keep the diversity of population and can be realized easily. The results show that the new algorithm is effective for solving multi-modal functions optimingations.