摘要
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。所以二者结合可互补。经试探分析,典型函数测试结果表明,混沌优化与量子遗传算法相结合全局寻优效果更佳。
Quantum genetic algorithm is an efficient parallel algorithm, but it drops into local optimum easily. The ergodicity of chaotic optimization can avoid this situation, the randomicity and the order of the algorithm can provide plenty space. So the integrate of two algorithm can behave better, which is demonstrated by the results from typical function test.
出处
《西南科技大学学报》
CAS
2005年第3期1-4,共4页
Journal of Southwest University of Science and Technology
关键词
混沌优化
量子遗传算法
优化
chaotic optimization
quantum genetic algorithm
optimization
