基于遗传珊瑚礁优化算法的负载均衡问题

Load Balancing Problem Based on Genetic Coral Reef Optimization Algorithm

基于珊瑚礁优化算法,通过在种群的每次进化过程中引入遗传算法中的交叉和变异算子,提出一种遗传珊瑚礁优化算法,并将改进的遗传珊瑚礁优化算法运用到负载均衡中,有效解决了算法过早收敛的问题,提升了算法的优化性能.对比经典遗传算法、珊瑚礁优化算法等群智能算法,在CloudSim上仿真实验结果表明,遗传珊瑚礁优化算法优化负载均衡策略取得了满意的结果,提升了资源能耗利用率,均衡了控制策略.

Based on the coral reef optimization algorithm,we proposed a genetic coral reef optimization algorithm by introducing crossover and mutation operators in genetic algorithm into each evolution process of population.The improved genetic coral reef optimization algorithm was applied to load balancing.The algorithm effectively solves the problem of premature convergence and improves the optimization performance of the algorithm.Comparing swarm intelligence algorithms such as classical genetic algorithm and coral reef optimization algorithm,simulation results on CloudSim show that the genetic coral reef optimization algorithm achieves satisfactory results in optimizing load balancing strategy,thus improving the utilization rate of energy consumption and balancing the control strategy.