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Study on Resources Scheduling Based on ACO Allgorithm and PSO Algorithm in Cloud Computing

机译:基于ACO AllGorithm和PSO算法在云计算中的资源调度研究

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It improves the algorithm because of the shortcoming that the ACO algorithm is easy to fall into local optimal solution in the cloud computing resource scheduling. The improved algorithm makes particle optimization inosculated into ant colony algorithm, which first finds out several groups of solutions using ACO algorithm according to the updated pheromone, and then gets more effective solutions using PSO algorithm to do crossover operation and mutation operation so as to avoid the algorithm prematurely into the local optimal solution.
机译:它改善了算法,因为ACO算法容易落入云计算资源调度中的局部最佳解决方案。改进的算法使粒子优化归咎于蚁群算法,首先使用根据更新的信息素的ACO算法发现几组解决方案,然后使用PSO算法获得更有效的解决方案,以进行交叉操作和突变操作,以避免算法过早地进入了本地最佳解决方案。

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