dynamic canonical descent(DCD) algorithm is able to avoid being trapped by local optimization

and do not assume the cost function to be differentiable

if firstly given a appropriate convex space interval; the algorithm can converge to a least point which lies in the given convex space interval; the algorithm of global optimization is shown on the numerical experimentation and the application to the rock and soil project for back analysis; and it is proved that the new algorithm would converge to the global best point quickly with a good numerical stability and credible results.