基于搜索空间大小的动态变异算子差分进化算法

差分进化算法（DE）是一种较新的进化计算技术，具有概念简单、易于实现、收敛速度快等优点，得到了广泛的关注和应用.为了解决经典DE计算开销大，参数设置与问题本身过于相关等缺陷，提出了一种改进的差分进化算法（IDE），它采用了一种动态变异算子，可根据进化代数的增加，基于搜索空间大小，实时地调整变异步长，从而提高算法的求解精度.通过在MATLAB仿真环境下对著名的基准测试函数分别进行求解，将改进后的算法和已有的多种优化算法进行比较，结果表明，改进的IDE算法性能明显优于已知的算法，证明动态变异是一种有效的改进思路.

Differential Evolution with Dynamic Mutation Based on Search Space

Differential Evolution (DE) is a novel evolutionary computation technique, which has attracted much attention and wide applications for its simple concept, easy implementation and quick convergence. In order to tackle much overhead, problem-dependent parameters, etc and enhance the precision of classical DE, an Improved DE(IDE) algorithm is proposed by using an dynamical mutation operator adjusting the step size based on search space with evolution. Experiments of solving well-known benchmark functions in MATLAB show the improved approach outperforms existing algorithms, and dynamic mutation is a effective improvement ideas.