摘要： 为了研发更高性能的QoS单播路由算法，提出变异退火粒子群优化(MSAPSO)算法。MSAPSO算法中使用一种新的⊕算子，将粒子群优化(PSO)的迭代公式简化成一个公式。通过设计变异退火算子，将遗传算法的变异操作和模拟退火的Metropolis概率接受准则融入PSO，以改善粒子群的多样性和算法的收敛性。仿真结果表明MSAPSO在搜索成功率和收敛性上优于纯PSO算法和蚁群算法。

关键词: 单播路由算法, 服务质量, 粒子群优化, 模拟退火

Abstract: This paper presents a novel Mutable Simulated Annealing Particle Swarm Optimization(MSAPSO) algorithm for solving the QoS unicast routing problem. A new ⊕ operator is used in MSAPSO, which can simplify the iterative formulas of Particle Swarm Optimization(PSO) into a single one. In order to improve the diversity and the convergence of the algorithm, it designs a mutable Simulated Annealing(SA) operator, which joins the mutation operator of Genetic Algorithm(GA) and metropolis rules of SA into PSO. The results show that the MSAPSO is superior to PSO and Ant Colony Optimization(ACO) in convergence and searching success rate.

Key words: unicast routing algorithm, Quality of Service(QoS), Particle Swarm Optimization(PSO), Simulated Annealing(SA)

中图分类号: 

• TP311