Abstract: Memetic algorithm is a metaheuristic search method. It is often used to solve NP problems. In this paper, through the improvement and optimization of the genetic Memetic algorithm, combined with the characteristics of the intelligent test paper generation, a set of complete solution is put forward. The algorithm uses the Memetic algorithm framework; the global search strategy uses genetic algorithm of piecewise real number encoding; crossover and mutation operations are included in. The local search strategy algorithm using simulated annealing algorithm, solves the local optimization problem effectively. Through the comparison experiment of different algorithms, the experimental results show that the Memetic algorithm proposed in this paper can solve the problem of generating test paper quickly and efficiently, at the same time, the algorithm can improve the quality of test paper, and also can reduce the number of iterations and obtain the optimal solution more quickly.
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Key words: generating test paper intelligently, Memetic algorithm, genetic algorithm, simulated annealing algorithm