An Improved Genetic Algorithm for Intelligent Test Paper Generation

Considering the problem on generating test papers is multi-objective parameter optimization under multiple constraints. I proposed a new improved genetic algorithm based on the researches of the mathematical model of generating test paper after encoding segmented chromosome, confirming adaptability function, segmented group initialization, altering adaptive crossover probability and mutation probability and conserve optimization individuals. This method implemented generating test paper well, and the experimental results show that this improved genetic algorithm is more practical and effective compared to the common algorithm in the same conditions.