微型机与应用
微型機與應用
미형궤여응용
MICROCOMPUTER & ITS APPLICATIONS
2011年
23期
60-62
,共3页
混沌%自适应%遗传算法%早熟%QoS组播路由
混沌%自適應%遺傳算法%早熟%QoS組播路由
혼돈%자괄응%유전산법%조숙%QoS조파로유
chaos%auto-adapted%genetic algorithm%precocious%QoS muhicast routing
经典遗传算法在解决QoS组播路由问题时存在易发生早熟现象、进化后期搜索效率低以及收敛后稳定性差等不足，为此，在遗传算法中引入混沌优化以及自适应调整交叉与变异概率两个改良措施。仿真实验表明，改良后的算法性能优良，在收敛速度、最优解的质量以及收敛后稳定性等方面有很大的提高。
經典遺傳算法在解決QoS組播路由問題時存在易髮生早熟現象、進化後期搜索效率低以及收斂後穩定性差等不足，為此，在遺傳算法中引入混沌優化以及自適應調整交扠與變異概率兩箇改良措施。倣真實驗錶明，改良後的算法性能優良，在收斂速度、最優解的質量以及收斂後穩定性等方麵有很大的提高。
경전유전산법재해결QoS조파로유문제시존재역발생조숙현상、진화후기수색효솔저이급수렴후은정성차등불족，위차，재유전산법중인입혼돈우화이급자괄응조정교차여변이개솔량개개량조시。방진실험표명，개량후적산법성능우량，재수렴속도、최우해적질량이급수렴후은정성등방면유흔대적제고。
When the classic genetic algorithm is used to solve the QoS multicast routing problem, there are some insufficient fields, such as being prone to precocious phenomenon, low efficiency search at the late evolution and poor stability after convergence. So, two measures are taken for improvement in the genetic algorithms, which are the chaos genetic algorithm optimization and adaptive crossover and mutation probability. Simulation experiment results show that the performance of the improved alg orithm is excellenl, it has been greatly improved on the convergence rate, the optimal solution quality, convergence stability and so on.
