%0 Journal Article %1 noauthororeditor %A Nejad, Mohammad Reza Karami %D 2012 %J International Journal of Computer Science, Engineering and Applications (IJCSEA) %K Automata Generation Genetic Learning Multicaset Networks Next Quality Routing Service of %N 5 %P 10 %R 10.5121/ijcsea.2012.2507 %T USING LEARNING AUTOMATA AND GENETIC ALGORITHMS TO IMPROVE THE QUALITY OF SERVICES IN MULTICAST ROUTING PROBLEM %U http://airccse.org/journal/ijcsea/papers/2512ijcsea07.pdf %V 2 %X A hybrid learning automata–genetic algorithm (HLGA) is proposed to solve QoS routing optimization problem of next generation networks. The algorithm complements the advantages of the learning Automato Algorithm(LA) and Genetic Algorithm(GA). It firstly uses the good global search capability of LA to generate initial population needed by GA, then it uses GA to improve the Quality of Service(QoS) and acquiring the optimization tree through new algorithms for crossover and mutation operators which are an NP–Complete problem

@article{noauthororeditor, abstract = {A hybrid learning automata–genetic algorithm (HLGA) is proposed to solve QoS routing optimization problem of next generation networks. The algorithm complements the advantages of the learning Automato Algorithm(LA) and Genetic Algorithm(GA). It firstly uses the good global search capability of LA to generate initial population needed by GA, then it uses GA to improve the Quality of Service(QoS) and acquiring the optimization tree through new algorithms for crossover and mutation operators which are an NP–Complete problem}, added-at = {2019-05-29T09:44:20.000+0200}, author = {Nejad, Mohammad Reza Karami}, biburl = {https://www.bibsonomy.org/bibtex/2fbcfcc90931db48bcc9f04938b28d4a8/ijcsea}, doi = {10.5121/ijcsea.2012.2507}, interhash = {77c5623478d46da1c6e3e17ec9b500df}, intrahash = {fbcfcc90931db48bcc9f04938b28d4a8}, journal = {International Journal of Computer Science, Engineering and Applications (IJCSEA) }, keywords = {Automata Generation Genetic Learning Multicaset Networks Next Quality Routing Service of}, month = {October}, number = 5, pages = 10, timestamp = {2019-05-29T09:44:20.000+0200}, title = {USING LEARNING AUTOMATA AND GENETIC ALGORITHMS TO IMPROVE THE QUALITY OF SERVICES IN MULTICAST ROUTING PROBLEM}, url = {http://airccse.org/journal/ijcsea/papers/2512ijcsea07.pdf}, volume = 2, year = 2012 }