改进的粒子群优化算法在QoS选播路由中的应用

QoS选播路由问题是一个非线性的组合优化问题,已被证明是NP完全问题.提出一种基于改进的粒子群优化的多QoS选播路由算法.算法引入一种特殊相加算子,让较差的路径能够不断向较好的路径学习,使算法尽可能向全局最优者靠近;设计一种随机变异算子,通过对全局极值进行随机变异,保证了粒子的多样性,提高了算法跳出局部最优解的能力.实验结果表明,该算法是可行和有效的,能够在资源预留的基础上较好地满足用户对带宽和时延的要求.

Application of an Improved Particle Swarm Optimization Algorithm in QoS Anycast Routing

QoS anycast routing problem is a nonlinear combination optimization problem, which is proved to be a NP complete prob-lena. Based on improved particle swarm optimization algorithm, a QoS anycast routing algorithm is proposed. This algorithm uses a special add operator to make the worst path learning from the better path in order to approach to global optimal path. To guarantee the diversity of particles and increase the algorithm's ability to skip out of local optimal solution quickly, a random mutation operator is designed to mutate global optima randomly. The experimental results illustrate that the algorithm is feasible and effective, and it can satisfy the need of the user for bandwidth and delay on the basic of resource reservation.