Research on Optimization of Intelligent Assignment of Crane Task Priority

The collision problem that occurs during the scheduling process of the crane is generally solved by prioritizing In order to intelligently solve the problem of task prioritization in the process of crane scheduling, the task prioritization model is established by using support vector machine (SVM). Aiming at the difficulty of parameter setting in the process of SVM, a dynamic cuckoo search (DCS) algorithm is proposed. The algorithm optimizes the parameter setting of SVM. In order to solve the shortcomings of the cuckoo algorithm, the step size and discovery probability of the standard cuckoo algorithm are improved as the dynamic adaptive step size and dynamic discovery probability. The test function verifies that it has the advantages of fast convergence speed and strong local optimal ability. Finally, the DCS-SVM is used to establish the prioritization model. After experimental verification, the method is proved to be effective, and it can accurately and intelligently solve the priority division problem of the crane scheduling task.