CAJ | 학술논문

在以往方法研究的基础上．分析遗传算法中不同的遗传算子及其主要运行参数变异概率和交叉概率对求解问题的影响，对传统的遗传算法进行改进，提出改进型自适应遗传算法。实验结果表明，经过改进的遗传算法能够比较有效地避免算法的“早熟”收敛，能够以更大的概率获得问题的最优解，求解质量更为优良，提高算法的性能。
재이왕방법연구적기출상．분석유전산법중불동적유전산자급기주요운행삼수변이개솔화교차개솔대구해문제적영향，대전통적유전산법진행개진，제출개진형자괄응유전산법。실험결과표명，경과개진적유전산법능구비교유효지피면산법적“조숙”수렴，능구이경대적개솔획득문제적최우해，구해질량경위우량，제고산법적성능。
On the basis of the method researched in the past, analyses the effect of different genetic operator and their main operation parameters, such as probability of mutation and crossover probability, in solving problems in the genetic algorithm, improves the traditional genetic algorithm, and proposes the improved adaptive genetic algorithm. The experimental result shows that the improved genetic algorithm can effectively avoid the premature convergence, and obtain the optimal solution of the problem in a greater probability, so as to get the better solution quality, can improve the performance of the algorithm.