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基于双链量子遗传算法的多约束QoS组播路由算法 被引量:2

A QOS MULTICAST ROUTING ALGORITHM BASED ON DOUBLE CHAINS QUANTUM GENETIC ALGORITHM
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摘要 多约束QoS组播路由问题是NP完全问题。提出一种基于双链量子遗传算法的多约束QoS组播路由算法,该算法具有种群多样性、收敛速度快、并行性更高等优点,并对算法具体流程和实现方法进行了详细的描述。实验结果表明,与已有的遗传算法、量子遗传算法相比,该算法有搜索速度快、全局寻优能力强等优点。 Multi-constrained quality-of-service (QoS) routing is an NP complete problem. In this paper we propose a multi-constrained QoS multicast routing aI^gorithm which is based on double chains quantum genetic algorithm (DCQGA), the algorithm has the advantages of population diversity, fast convergence speed and better parallelism, etc. We also provide detailed description on specific processes and the implementation means of the algorithm. Experimental results show that compared with existing genetic algorithm and quantum generic algorithm, the proposed algorithm has the advantages of higher search speed and strong global optimisation ability.
出处 《计算机应用与软件》 CSCD 北大核心 2013年第1期250-252,300,共4页 Computer Applications and Software
关键词 组播路由 QOS 双链量子遗传算法 Multicast routing QoS DCQGA( Double Chains Quantum Genetic Algorithms)
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  • 1Muldenbein H. Parallel Genetic Algorithms in Combinatorial Optimization[A]. Computer Science and Operation Research--New Developments[M]. New York: Pergamon Press, 1992. 441-453.
  • 2Grefenstette J J, Coped R, Rosmaita B, et al. Genetic Algorithms for the Traveling Salesman Problem[A]. Proceedings of the First International Conference on Genetic Algorithms and Their Applications[C]. NJ: Lawrence Earlbaum Associate, 1985. 160-168.
  • 3Kristinsson K, Dumont G A. System Identification and Control Using Genetic Algorithms[J]. IEEE Trans on Sys, Man and Cybernetic,1992, 22(5): 1033-1046.
  • 4Holland J H. Genetic Algorithms and Classifier Systems: Foundations and Their Applicaitons[A]. Proceedings of the Second International Conference on Genetic Algorithms[C]. Hillsdale: Lawrence Erlbaum Associates, 1987. 82-89.
  • 5Krishnakumar K, Goldberg D E. Control System Optimization Using Genetic Algorithms[J]. Journal of Guidance, Control and Dynamics, 1992, 15(3): 735-740.
  • 6Rudolph G. Convergence Analysis of Canonical Genetic Algorithms[J]. IEEE Trans on Neural Networks, 1994, 5(1): 96-101.
  • 7Stumpf J D, Feng X, Kelnhofer R W. An Enhanced Operator-oriented Genetic Search Algorithm[A]. The First IEEE Conference on Evolutionary Computation[C]. Orlando; IEEE Press, 1994. 235-238.
  • 8Hesser J, Manner R. Towards an Optimal Mutation Probability for Genetic Algorithms[A]. Proceedings of the First Conference on Parallel Problem Solving from Nature[C]. Dortmund: Springer, 1990. 23-32.
  • 9Srinivas M, Patnail L M. Adaptive Probabilities of Crossover and Mutation in Genetic Algorithms[J]. IEEE Trans Syst, Man and Cybem, 1994, 24(4): 656-667.
  • 10Hey T. Quantum Computing: an Introduction[J]. Computing & Control Engineering Journal, 1999, 10(3) : 105-112.

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