For complexity and efficiency of the multi-objective optimization, we proposed the mobile distance field-driven adaptive\ncrowd optimization algorithm. In space, we modify the surface parameters based on the corresponding changes of the\ndistance field to obtain the moving target�s moving track and moving surface. When the curve of the moving\ntrack is changed, the x axis and the y axis of the moving track are adjusted adaptively. In this paper, the moving process\nis divided into three processes: the target dynamic crowd control, the crowd model algorithm, and the predictive control\nof linear time domain based on the moving target prediction and crowd control algorithm. Then, the multi-objective\noptimization algorithm of moving objects is proposed by using the crowd model to predict the status and the position\nof the target. The experimental results show the high accuracy, low complexity, and high efficiency of the proposed\noptimization algorithm.
Loading....