A Hybrid Multi-Objective Bat Algorithm for Solving Cloud Computing Resource Scheduling Problems

To improve the service quality of cloud computing, and aiming at characteristics resource scheduling optimization problems, this paper proposes a hybrid multi-objective bat algorithm. prevent algorithm from falling into local minimum, population is classified. The back-propagation based on mean square error conjugate gradient method used to increase loudness in search direction pulse emission rate. In addition, random walk lévy flight also optimal solution, thereby improving algorithm’s global capability. simulation results prove that proposed superior ant colony algorithm, genetic particle swarm cuckoo terms makespan, degree imbalance, throughput. cost slightly better than