摘要
为了解决传统遗传算法在求解多目标优化问题时存在的收敛速度慢并且易于陷入局部最小等问题,提出了一种求解多目标优化问题的正交多Agent遗传算法。设计了正交初始化算子、邻域竞争算子、正交交叉算子、变异算子,对传统遗传算法进行了改进。最后,通过标准测试函数的仿真结果表明,算法具有较好的收敛性,能够较快得到最优解。
To solve traditional genetic algorithm convergence is slow and easy to fall into local minimum problems in solving multi- objective optimization problem, an evolutionary algorithm, Orthogonal Multi- Agent genetic algorithm is proposed. Orthogonal initialization operator, neighborhood competition operator, orthogonal crossover operator and mutation operator are designed. The traditional genetic algorithm is improved. Finally, several standard test functions are used to test the algorithm and the simulation results show that the proposed algorithm has better convergence and the optimal solution can be quickly obtained.
作者
侯文人
HOU Wen-ren （College of Information Technology Engineering, Tianj in University of Technology and Education, Tianjin 300222, China）
出处
《电脑知识与技术》
2016年第3期162-163,168,共3页
Computer Knowledge and Technology
关键词
多目标优化
遗传算法
收敛
正交
最优解
multi objective optimization
genetic algorithm
convergence
orthogonal
the optimal solution
