为减少免疫算法应用时的计算量,对免疫算法的原理进行研究,提出一种基于药物辅助的免疫算法,并研究其在函数优化方面的应用.类比人体免疫系统机理,增加药物治疗环节.改进算法是将原始目标函数进行分割,当算法寻找到某一局部极小值后,在原始目标函数的基础上更新搜索区域,提高收敛速度,降低计算量.最后通过仿真实验验证了所提出算法在多峰函数的寻优问题应用中的可行性和优越性. In order to reduce the computational complexity of immune algorithm, the principle of immune algorithm is studied, and a drug-based immune algorithm is proposed and its application in function optimization is studied. The algorithm divides the original objective function, when the algorithm finds a certain local minimum, it updates the search area based on the original objective function to improve the convergence rate and reduce the computational complexity.Finally, the simulation results show that the proposed algorithm The feasibility and superiority in the application of multi-peak function optimization problem.