Parallel simulated annealing genetic algorithm for optimizing BP neural network
一种用于BP网络优化的并行模拟退火遗传算法

A Parallel Simulated Annealing Genetic Algorithm(PSAGA) was given for the optimization of 3 levels BP neural network.Simulated annealing(SA) method was applied in fitness scaling,genetic operator was improved by ranking selection which copied the fittest,heuristic crossover and multi nonuniform mutation,and SA was used as the state generator.The idea of parallel evolution was combined into PSAGM.Simulation to recognition of English letters proved PSAGM was better than simple genetic algorithm in global search,local search and speed of convergence.