Title :
A learnable genetic algorithm for QoS multicast routing
Author :
Xiao-Jun, Feng ; Fang, Liu
Author_Institution :
Comput .Sch., Xidian Univ., Xi´´an, China
Abstract :
By improving the conventional genetic algorithm, we put forward a learnable genetic algorithm combining machine learning and genetic algorithm. The central idea of the algorithm is that it generates new individuals by processes of hypothesis generation and instantiation, rather than by mutation and/or recombination as in conventional genetic algorithms. The algorithm is then used for the bandwidth-delay-constrained least-cost multicast routing problem. The features of this new algorithm are simplicity and effectivity.
Keywords :
delay estimation; genetic algorithms; multicast communication; quality of service; telecommunication network routing; QoS multicast routing; bandwidth-delay-constrained least-cost problem; effectivity; hypothesis generation; instantiation; learnable genetic algorithm; machine learning; simplicity; Bandwidth; Delay; Genetic algorithms; Genetic mutations; Heuristic algorithms; Machine learning; Machine learning algorithms; Multicast algorithms; Routing; Tree graphs;
Conference_Titel :
Signal Processing, 2002 6th International Conference on
Print_ISBN :
0-7803-7488-6
DOI :
10.1109/ICOSP.2002.1180987