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基于QPSO的QoS组播路由算法
引用本文:秦洁,须文波.基于QPSO的QoS组播路由算法[J].计算机应用,2007,27(2):285-287.
作者姓名:秦洁  须文波
作者单位:江南大学,信息工程学院,江苏,无锡,214122
摘    要:对带宽、延时、延时抖动约束最小代价的QoS组播路由问题进行了研究,提出一种基于量子行为微粒群优化(QPSO)算法来设计路由优化算法。该算法采用一种节点序列编码方案,将路由优化问题转化成一种准连续优化问题,并采用罚函数处理约束条件。应用QPSO算法求解QoS组播路由问题的算例,并与遗传算法和改进后的遗传算法进行比较。计算机仿真实验证明,该算法可以更有效地求得QoS组播路由问题的优化解,可靠性较高。

关 键 词:组播路由  服务质量  路由优化  微粒群优化算法  基于量子行为的微粒群优化算法
文章编号:1001-9081(2007)02-0285-03
收稿时间:2006-08-15
修稿时间:2006-08-22

QoS multicast routing optimization algorithm based on QPSO algorithms
QIN Jie,XU Wen-bo.QoS multicast routing optimization algorithm based on QPSO algorithms[J].journal of Computer Applications,2007,27(2):285-287.
Authors:QIN Jie  XU Wen-bo
Affiliation:School of Information Engineering, Southern Yangtze University, Wuxi Jangsu 214122, China
Abstract:To study the bandwidth, delay, delay jitter, and packet loss constrained least-cost multicast routing problem, a quantum-behaved particle swarm optimization algorithm was proposed. The QoS multicast routing optimization problem was changed into a quasi-continuous problem by using a node series encoding method. Constrained terms in the problem were processed by the penalty function. This proposed algorithm was applied to illustrate its higher searching efficiency in comparison with standard genetic algorithm and advanced genetic algorithm for the routing optimization problem. Computer simulations have verified that this algorithm is effective and efficient.
Keywords:multicast routing  QoS  routing optimization  particle swarm optimization algorithms  Quantum-behaved Particle Swarm Optimization (QPSO)
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