摘要
针对遗传算法的不足,提出将禁忌搜索方法、免疫算法、遗传算法融和的多目标混合进化算法。该算法引入禁忌搜索法,避免了传统遗传算法早熟现象的发生;引入基于浓度的自适应变异操作,克服算法由于变异概率不变导致的求解过程长,解的多样性差的缺陷;引入外部精英集,避免最优解的丢失,通过ZDT系列测试函数的仿真实验并与NSGA-Ⅱ算法进行比较,验证了算法的有效性。
A multi-objective hybrid evolutionary algorithm（MHEA）was put forward aiming at the shortcomings of the traditional genetic algorithm,which combines taboo search algorithm,immune algorithm and genetic algorithm.This algorithm avoids the premature phenomenon of the traditional genetic algorithm through importing the taboo search algorithm.The operator of adaptive mutation based on the density overcomes the problem of long solving process caused by the constant mutation probability and bad diversity of the solution.Then external elite set was introduced to avoid the loss of the optimal solution.Finally the simulation of ZDT series test functions and the comparison with NSGA-Ⅱalgorithm verifies the effectiveness of the algorithm.
出处
《计算技术与自动化》
2015年第1期76-80,共5页
Computing Technology and Automation
