Application of Improved Genetic Algorithm in Optimization Computation
Zhu Si-ru · 2009
Some practical problems usually contain multiple optima, of which some are local and some global, and traditional method is easily getting trapped at local optimum. To avoid this phenomena, genetic algorithm (GA) is introduced, significantly faster & robust at numerical optimization and is more likely to find a function's true global optimum. In this paper, improved Genetic Algorithm (IGA) is introduced to solve global optima problems. The experiment shows that performance of IGA is better than traditional methods and SGA.