A Dynamic Byte Encoding Genetic Algorithm for Numerical Optimization
Xianyue Gang, Hongyan Li, Shufeng Wang · 2008
Based on binary encoding and dynamic parameter encoding methods, taking advantages of the binary logical operation characteristic of computer, a dynamic byte encoding genetic algorithm (DBE-GA) is proposed for numerical optimization. The decoding, crossover, mutation and dynamic adjusting of search region are implemented high efficiently in storage mode, gene mode and apparent mode respectively. The measurement of population convergence requires large computational efforts for search with many bits or strings. A look-up technique is developed by using binary logical operation to overcome this bottleneck. The outstanding performance of DBE-GA has been evaluated with numerical tests.