Multichannel transcranial magnetic stimulation (mTMS) is a therapeutic method to improve psychiatric diseases, which has a flexible working pattern used to different applications. In order to make the electric field distribution in the brain meet the treatment expectations, we have developed a novel multi-swam particle swarm optimizer (NMSPSO) to optimize the current configuration of double layer coil array. To balance the exploration and exploitation abilities, three novel improved strategies are used in NMSPSO based on multi-swarm particle swarm optimizer. Firstly, a novel information exchange strategy is achieved by individual exchanges between sub-swarms. Secondly, a novel leaning strategy is used to control knowledge dissemination in the population, which not only increases the diversity of the particles but also guarantees the convergence. Finally, a novel mutation strategy is introduced, which can help the population jump out of the local optimum for better exploration ability. The method is examined on a set of well-known benchmark functions and the results show that NMSPSO has better performance than many particle swarm optimization variants. And the superior electric field distribution in mTMS can be obtained by NMSPSO to optimize the current configuration of the double layer coil array.

多通道经颅磁刺激（mTMS）是一种改善精神疾病的治疗方法，具有适用于不同应用的灵活工作模式。为了使大脑中的电场分布符合治疗预​​期，我们开发了一种新型的多组粒子群优化器（NMSPSO）来优化双层线圈阵列的当前配置。为了平衡探索和开发能力，在基于多群粒子群优化器的 NMSPSO 中使用了三种新颖的改进策略。首先，通过子群之间的个体交换实现了一种新颖的信息交换策略。其次，采用新颖的学习策略控制群体中的知识传播，既增加了粒子的多样性，又保证了收敛性。最后，引入了一种新的变异策略，可以帮助种群跳出局部最优，以获得更好的探索能力。该方法在一组众所周知的基准函数上进行了检查，结果表明 NMSPSO 比许多粒子群优化变体具有更好的性能。NMSPSO 可以获得 mTMS 中优越的电场分布，以优化双层线圈阵列的电流配置。