面向可靠性冗余优化的自适应差分进化算法

针对可靠性冗余优化问题中解的精度低及算法早熟收敛的问题,提出一种自适应的差分进化算法.该算法在原始差分进化算法的基础上修改了变异算子和交叉算子;在进化过程中,缩放因子F和交叉概率CR分别由三角函数实现自适应调节,以提高可行解的多样性及算法的收敛速度.解决了可靠性冗余优化问题解的精度低及早熟收敛问题.实验结果表明,该算法在解决可靠性冗余优化问题上不仅提高了解的精度,且具有更好的稳定性及更快的收敛速度.

Adaptive Differential Evolution Algorithm forReliability Redundancy Optimization

Aimming at low accuracy solutions and the premature convergence problem in the reliability redundancy optimization problems, we proposed an adaptive differential evolution algorithm, which modified mutation operatorand crossover operator on the basis of the original differential evolution algorithm. In the process of evolution, the scale factor F and crossover probability CR were adaptively adjusted by trigonometric function respectively to improve the diversity of the feasible solution and convergence rate of the algorithm. It solved the low accuracy solutions and premature convergence problems of the reliability redundancy optimization problems. Experimental results show that the algorithm not only improves the accuracy of solution, but also has better stability and faster convergence rate for solving the reliability redundancy optimization problem.