Abstract

We propose a novel hybrid genetic algorithm (GA) based on such techniques as clustering, sharing, crowding, and adaptive probability. The proposed GA can effectively solve multimodal optimization, including the global and local optima in the distributed multipump Raman amplifier (DMRA). The simulation results show that the optimal signal bandwidth Delta lambda can be evidently broadened by means of increasing the number of pumps and that Delta lambda decreases with the increase of Raman gain and the improvement of the flatness property. The optimal results show that the hybrid erbium-doped fiber amplifier and DMRA can availably overcome the weakness of pure DMRA and that both higher gain and broader bandwidth can be realized in hybrid amplifiers simultaneously.

© 2003 IEEE

Efficient algorithm and optimization for broadband Raman amplifiers

Xueming Liu and Yanhe Li
Opt. Express 12(4) 564-573 (2004)

Optimal design of DFG-based wavelength conversion based on hybrid genetic algorithm

Xueming Liu and Yanhe Li
Opt. Express 11(14) 1677-1688 (2003)

Design of a flat-gain multipumped distributed fiber Raman amplifier by particle swarm optimization

Alireza Mowla and Nosrat Granpayeh
J. Opt. Soc. Am. A 25(12) 3059-3066 (2008)

Efficient use of hybrid Genetic Algorithms in the gain optimization of distributed Raman amplifiers

B. Neto, A. L. J Teixeira, N. Wada, and P. S. André
Opt. Express 15(26) 17520-17528 (2007)

Optimized design of two-pump fiber optical parametric amplifier with two-section nonlinear fibers using genetic algorithm

Mingyi Gao, Chun Jiang, Weisheng Hu, and Jingyuan Wang
Opt. Express 12(23) 5603-5613 (2004)