Research of the intelligence test paper generation based on improved adaptive coarse-grained parallel genetic algorithm

Conventional mathematics methods are extensively adopted in the most test paper generation systems, but these methods can´t deal with multi-objective optimization question of more than one constrains effectively. This paper proposes an improved parallel GA(Genetic Algorithm) with good adaptability and universal applicability, which is used in test paper generation. The experiment results indicate that the algorithm is more adaptively and faster than conventional parallel GA, and improve the intelligent level of the test paper generation system effectively.