Task scheduling optimization method and device

The invention discloses a task scheduling optimization method and device. The method comprises the following steps: receiving an input parameter; judging the times of recording the input parameters in a training module; if the times is smaller than a preset threshold value, finishing a workflow by adopting a random task execution sequence according to the dependency relationship among preset tasks, forming an incidence relation among the input parameter, the task execution sequence of finishing the workflow, and data on time consumed to finish the workflow, recording the incidence relationship in the training module in a newly increased manner; otherwise, selecting the task execution sequence with the shortest time consumed on average in the training module to finish the workflow, forming an incidence relation among the input parameter, the task execution sequence of finishing the workflow, and the data on time consumed to finish the workflow, and recording the incidence relation in the training module in a newly increased manner. A developer does not need to care about task execution states and complex dependency relationships, learns the task processing efficiency by himself or herself, and optimizes the execution path.