Function Optimization Problem Based on Genetic-Neural Network Algorithm

A genetic-neural network algorithm for optimum design is proposed. In the algorithm, the global property of genetic algorithm(GA) and the parallelism of artificial neural networks ( AN2) are combined; GA provides global initial solution, form which AN2 obtains the final solutions. Thus, the defects of slow convergence with GA and easily falling into local solutions with AN2 can be overcome .An applied example shows global, convergence and parallelism for the algorithm.