(N+M)容错系统优化模型求解的父代保留免疫遗传算法

针对(N M)容错系统优化模型复杂非线性的特点,结合免疫遗传算法和父代保留策略,提出了模型求解的父代保留免疫遗传算法。该算法在进行交叉和变异操作后,新产生的个体不覆盖父代个体,扩展种群进行基于矢量距浓度机制的选择操作,这样可避免较优个体的损失,增强种群的多样性,提高算法的搜索能力及收敛性能。算法性能分析揭示了算法性能改善的机理。优化模型求解结果表明,该文提出的算法较免疫遗传算法在寻优精度和收敛速度方面有一定改善。

Optimization of (N+M) fault-tolerant systems

The elder-keeping immune genetic algorithm,which combines the immune genetic algorithm with the elder-keeping strategy,was used to solve the non-linear optimization model of(N M) fault-tolerant systems.The algorithm,in which the new individuals produced in the crossover and mutation operations do not replace the elders and take part in vector distance-based reproduction with the last population,enhances the elder-keeping immune genetic algorithm by improving its population diversity,its search ability and convergence.The performance was analyzed to improve the convergence.Tests show that the algorithm has better performance for solving the optimal model than the immune genetic algorithm in forms of search precision and convergence efficiency.