Background: Min-min and max-min algorithms were combined on the basis of the traditional
genetic algorithm to make up for its shortcomings.
Methods: In this paper, a new cloud computing task-scheduling algorithm that introduces min-min
and max-min algorithms to generate initialization population, selects task completion time and load
balancing as double fitness functions, and improves the quality of initialization population, algorithm
searchability and convergence speed, was proposed.
Results: The simulation results proved that the cloud computing task-scheduling algorithm was superior
to and more effective than the traditional genetic algorithm.
Conclusion: The paper proposes the possibility of the fusion of the two quadratively improved algorithms
and completes the preliminary fusion of the algorithm, but the simulation results of the new
algorithm are not ideal and need to be further studied.