基于改进自适应遗传算法的智能组卷算法

传统的组卷算法具有组卷速度慢、成功率低和组卷质量不高等缺陷。为了解决该问题,提出一种基于正弦形式自适应遗传算子的改进遗传算法的组卷算法,理论分析和实验结果表明,与基本遗传算法和自适应遗传算法相比,改进的遗传算法更能满足组卷的实际需求,在全局搜索性能、收敛速度和组卷成功率较基本遗传算法和自适应遗传算法有显著提高,证明了改进算法的有效性和优越性。

Algorithm of Composing Test Paper Based on Improved Self-adaption Genetic Algorithm

Traditional algorithms of composing test paper have the disadvantages of slow convergence,low success rate and quality.To solve these problems,an algorithm based on improved adaptive genetic algorithm is proposed.Both the theoretical analysis and the experimental comparison show that improved genetic algorithm can satisfy the needs for actual examinations.Improved genetic algorithm can obviously improve the ability of global research,the convergence speed and the quality than tradition genetic algorithm and self-adaption genetic algorithm.It proves that the improved algorithm is effective and superior.