摘要
提出了一种求解约束优化问题的微分进化算法。该算法使得种群在演化过程中能保持较好的多样性,且参数设置简单,不容易陷入局部最优,并能在较短时间内找到问题的最优解。在对多个测试函数的数值模拟中都得到了较好的结果,体现了该算法的有效性、通用性和稳健性。
An approach,CDE,is presented to handle constrained function optimization problems using differential evolutionary algorithms.The approach can maintain population diversity and simple parameter setting which makes the CDE more likely to find the global optimum in evolutionary process.It enables us to find the optimal solution within a fairly short period of time.The preferable results can be gotten in some benchmark function’s numerical simulations.The results show that the approach is an effective,general and robust method.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第15期51-52,68,共3页
Computer Engineering and Applications
关键词
算法
函数优化
微分进化
约束处理
algorithm
function optimization
differential evolution
constraint handling
