Cross-Entropy Optimization for the Design of Fiber Bragg Gratings

This paper considers the synthesis problem of a low-dispersion fiber Bragg grating (FBG) filter. This problem can be formulated as a nonlinear objective problem in practice. However, solving this problem with traditional methods is difficult because of its multimodal and ill-conditioned character. Inspired by the efficient ability of cross-entropy optimization (CEO) method to find near-optimal solutions in large search spaces, we propose the application of CEO method to search for design variables to satisfy the target design criteria. Computer simulation results show that the proposed CEO method can successfully achieve the target values of the design specifications. It also provides a reliable convergence to the near-optimum solution. These findings indicate that the CEO algorithm is more appropriate for the FBG filter design compared with conventional particle swarm optimization method.