摘要
在组卷策略中,多重约束目标的智能组合优化问题一直是人们研究的热点.大多数的优化算法都是基于传统的遗传算法,这些算法的适应度不高,并且交叉算子和变异算子对适应度的影响很大.针对这些缺陷,本文提出了一种新的优化算法DNA_YH算法,该算法将DNA编码引入到多重约束目标的组合优化问题中,并完成了DNA编码、初始化种群、个体适应度计算和遗传操作的优化过程.经过实验证明DNA_YH算法的最优适应度高于其他相关算法,并且交叉算子和变异算子对适应度的影响都很小,得到了较好的优化效果.
In the formation of a test paper, the combination optimization problems of multiple objective constraints have been studied. Most optimization algorithms are based on the traditional genetic algorithm, the adaptation of these algorithms is not high, and is impacted by the crossover operator and mutation operator on the fitness. Aiming at these defects, this paper presented a new optimization algorithm DNA_YH algorithm, which encoded DNA code into combination optimization problem of multiple constraint objective, and finished DNA coding, population initializing, the individual fitness computing and genetic operation optimizing process. Exper- iments proved that the fitness of DNA_YH algorithm is higher than those of other algorithms, and the crossover operator and mutation operator have very small influences on the fitness.
出处
《佳木斯大学学报(自然科学版)》
CAS
2012年第1期91-93,共3页
Journal of Jiamusi University:Natural Science Edition
基金
黑龙江省教育厅科学技术研究项目资助(11553084)
关键词
DNA编码
多重约束目标
组合优化
优化算法
DNA coding
multiple constraint objective
combination optimization
DNA_YH