基于混沌优化的量子遗传算法

量子遗传算法是一种高效的并行算法,但它有时会陷入局部极值。混沌优化的遍历性可作为搜索过程中避免陷入局部极小值的一种优化机制,随机性和规律性使它具有丰富的时空动态。对二者互补地结合作了试探分析,典型函数测试结果表明,混沌优化与量子遗传算法相结合的全局寻优效果更佳。

Quantum genetic algorithm based on chaotic optimization

Quantum genetic algorithm is an efficient parallel algorithm, but it drops into local optimum easily. The ergodicity of chaotic optimization can avoid it from dropping into local optimum easily; the randomicity and the order of it can provide plenty of temporal and spatial dynamic. So the integration of two algorithms can behave better. The test results of typical function demonstrate that it is better than the single method.