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将鹰策略和差分进化结合用于解决可靠性冗余优化问题.优化过程分为两个阶段:第一阶段使用Lévy飞行在解空间中进行全局搜索,第二阶段使用差分进化算法在前阶段得到的有前途解的周围进行快速的局部搜索.同时,修改了差分进化算法的变异算子和交叉算子以提高局部搜索的性能.该算法较好地实现了全局搜索和局部搜索的平衡,既有利于跳出局部最优,又可以加快局部收敛.通过对可靠性冗余优化的两个基本问题的实验表明,所提出的算法在解决可靠性冗余优化问题上是有效的.
The eagle strategy and differential evolution are used to solve the problem of reliability redundancy optimization.The optimization process is divided into two stages: the first stage uses Lévy flight to do global search in solution space, the second stage uses differential evolution algorithm to get Of the solution.Furthermore, the mutation operator and the crossover operator of the differential evolution algorithm are modified to improve the performance of the local search.The algorithm can well achieve the balance of the global search and the local search, and both Which is good for jumping out of the local optimum and accelerating the local convergence.Experiments on two basic problems of reliability redundancy optimization show that the proposed algorithm is effective in solving the problem of reliability redundancy optimization.