一种基于种群多样性的新型自适应遗传算法  

A new adaptive genetic algorithm based on population diversity

作　　者：王剑楠 崔英花[1] WANG Jiannan;CUI Yinghua(Institute of Information Communication,Beijing Information Science and Technology University,Beijing 100101,China)

机构地区：[1]北京信息科技大学信息与通信工程学院,北京100101

出　　处：《太赫兹科学与电子信息学报》2023年第5期671-676,共6页Journal of Terahertz Science and Electronic Information Technology

基　　金：北京市自然科学基金面上项目(4202024);国家自然科学基金资助项目(61340005);重点研究培育基金资助项目(2020KYNH213)。

摘　　要：为克服传统自适应遗传算法易出现未成熟收敛的问题,提出一种新型基于种群多样性的自适应遗传算法。解决未成熟收敛问题的关键是避免算法在寻找到最优解前种群多样性的丧失。为适应进化过程中种群多样性的变化,提出了包含方差因子和种群熵因子的交叉概率和变异概率公式。根据种群收敛情况相应地调整交叉概率及变异概率,在不破坏种群优良基因模式的同时保持种群的多样性。通过标准函数测试与已有算法进行对比,结果表明,所提算法相较于已有算法,在保证收敛精确度的同时提高了收敛速度,有效克服了“早熟”等问题。In order to tackle the problem of“premature”in traditional adaptive genetic algorithms,a new adaptive genetic algorithm based on population diversity is proposed.The key to solve the immature convergence problem is to avoid the loss of population diversity before the algorithm finds the optimal solution.In order to adapt to the changes in population diversity in the evolutionary process,the crossover probability and mutation probability formulas including the variance factor and the population entropy factor are designed.According to the population convergence,the crossover probability and mutation probability are adjusted accordingly to maintain the diversity of the population without destroying the good gene model of the population.By testing standard functions and comparing them with existing algorithms,the results show that the improved algorithm not only can ensure the convergence accuracy,but also increase the convergence speed,and effectively overcome the“premature”problems.

关 键 词：自适应 遗传算法 未成熟收敛 种群多样性 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]