组播最优QoS划分问题及其混合遗传算法

Multicast Optimal QoS Partition Problem and its Hybrid Genetic Algorithm

最优QoS划分研究基于性能的价格体系下的资源分配问题,组播最优QoS划分(MOPQ)是将组播树上端到端QoS要求划分到本地链路,使得总代价最小。研究了求解MOPQ问题的遗传算法,设计了由树代价与叶结点惩罚因子构成的适应度函数,提出了双子群混合遗传算法。该算法充分利用了遗传算法的全局搜索优势,模拟退火算法的局部搜索优势以及双子群的协作优势。仿真结果表明该算法的有效性。

Optimal QoS partition is a problem of optimal resource allocation in the context of performance dependent cost. Multicast optimal QoS Partition （MOPQ） is how to partition the end-to-end QoS requirements of a tree into local requirements, such that the overall cost is minimized. GA algorithms for MOPQ problems were studied, a fitness function based on tree cost and leaf nodes punish factor was designed, and a dual subpopulation hybrid genetic algorithm was proposed. This algorithm took advantage of GA＇s global search ability and simulated annealing algorithm＇s local search ability. Subpopulations cooperation further improves performance. Simulation results prove this algorithm＇s efficiency.