Research On And Application Of The Multi-constraits Goal Optimization Problem Based On Genetic Algorithm

The optimization algorithm becomes popular in the recent years, such as the artificial neural network, chaotic and genetic algorithms and taboo search involving maths , physics, biology etc. It provides as a new method to resolve complicated problems and gains success in lots of fields.Compared with the other intelligent optimization algorithms, Genetic algorithm has manifest advantages. Firstly, it can easily avoid premature convergence, and even in the situation of then discontinurity of fitness function , accompanied with noises, it also has a higer probability to find the optimized solution with that situation . Secondly , owing to the intrinsic parallel quality of GA ,it is very fit for large scale parallel distributed processing .This paper mainly studies the use of GA in the Combination optimization ,makes a detailed discuss and a deep analysis on the multi - constraints goal optimization based on GA , and then puts forward a solution to "the intelligent test paper forming" as an example.