CAJ | 학술논문

针对传统基于简单遗传算法的组卷系统收敛速度慢，组卷质量较差等缺陷，设计一种基于改进小生境遗传算法的自适应组卷系统。首先依照组卷约束权重比，生成适应度值较高的初始种群，其次对选择策略进行优化，引入小生境预选机制以维持种群多样性，防止过早收敛。再次根据组卷特点改进交叉算子和变异算子，根据种群进化情况，自动调整交叉概率和变异概率。最后经过若干迭代后达到终止条件，以自适应方式生成目标试卷。实验结果证明，与简单遗传算法相比，改进的遗传算法在收敛速度和组卷质量上均有显著的提高。
침대전통기우간단유전산법적조권계통수렴속도만，조권질량교차등결함，설계일충기우개진소생경유전산법적자괄응조권계통。수선의조조권약속권중비，생성괄응도치교고적초시충군，기차대선택책략진행우화，인입소생경예선궤제이유지충군다양성，방지과조수렴。재차근거조권특점개진교차산자화변이산자，근거충군진화정황，자동조정교차개솔화변이개솔。최후경과약간질대후체도종지조건，이자괄응방식생성목표시권。실험결과증명，여간단유전산법상비，개진적유전산법재수렴속도화조권질량상균유현저적제고。
For traditional paper constructing algorithm based on Simple Genetic Algorithm has defects such as low convergence rate, unsatisfactory quality and so on, we designed an efficient paper constructing system based on Improved Genetic Algorithm. Firstly, it generated the relatively higher fitness initial population according to the ratio of paper restraints. Secondly, it optimized the select strategy, imported the niche pre-select mechanism to preserve population's diversity and prevented the premature convergence. Thirdly, it improved the crossover operator and mutation operator according to the character of paper constructing, and as the evolution of population carrying on, it could adapt the crossover probability and mutation probability automatically. Finally, it achieved the terminal condition after some iterations, and generated target papers with the self-adaptive method. Experimental results showed that the improved Genetic Algorithm performed much better in convergence speed and paper constructing quality compared to Simple Genetic Algorithm.