基于Tabu搜索和变区域遗传算法的组卷问题研究

针对目前大型题库中组卷算法效率低的问题，给出了多目标约束条件下的组卷问题数学模型，提出了基于Tabu搜索和变区域遗传算法的TS-CAGA算法。本算法用遗传算法作全局搜索，用禁忌搜索算法作局部搜索，给出了搜索区域动态变化的条件，通过种群规模自适应调整，可以加快收敛速度和避免局部最优化。实验结果表明，算法的组卷效率和选题质量有显著提高。

Research on algorithm of forming test papers based on Tabu search and changing area GA

To improve poor efficiency in generating examination papers from a large item bank, a model of multiple assessment criteria is given in this paper, and a TS-CAGA algorithm based on Tabu search and changing area GA is proposed. In this algorithm, GA is used for global search, and Tabu search algorithm is applied to local search. The condition for changing area dynamically is presented. Meanwhile, an adaptive adjustment method of the population size is made to speed up convergence and avoid converging to local optimum. Experiment results indicate that this algorithm is more effective and of better quality in forming test papers.