Abstract:
Aiming at the shortcomings that it is difficult to obtain feasible points, low optimization efficiency, slow convergence speed, and difficult to effectively balance the global and local search behaviors, a black- box constrained global optimization method of sequential Kriging (BCGO-SK) is proposed. In the absence of initial feasible sampling points, the proposed method can quickly and efficiently explore promising feasible points, and obtain the global optimal feasible solution by satisfying all constraints under the efficient, stable and reliable sampling point. The test results on benchmark functions and a simulation of fuel cell vehicle energy control strategies verify the effectiveness and practicability of the proposed method.