【摘要】 根据生物免疫系统机理推导出一类数学优化结构模型的免疫算法。此算法结合遗传算法的进化操作和生物免疫中的浓度机制,通过抗体的期望繁殖率实现对抗体的促进和抑制,改善未成熟收敛。该算法用于求解Rosenbrock函数,并且与遗传算法进行了比较,结果表明,该免疫算法不仅收敛,而且具有较高的全局和局部搜索能力和收敛速度。更多还原

【Abstract】 An immune algorithm of a mathematically optimal structure model is derived based on the natural immune system mechanism. The algorithm combines the evolution function of traditional genetic algorithms and the density mechanism in creatures’ immune procedure. The adjustment of antibodies is realized by the expected breed rate to improve the premature convergence. The algorithm is used to solve for the optimization of Rosenbrock function, and compared to a genetic algorithm. The results show that the immune algorithm performs better in the aspect of global and local search ability and search speed.更多还原