中文摘要：

在Median-based模型的基础上，建立了带容量约束的配送中心选址模型，并给出求解算法。为避免算法早熟，提出一种异质多群体粒子群算法，将种群划分为主群和若干异质拓扑结构子群，平衡算法的开发与探索能力。设计了二进制与浮点数混合并行编码，将改进算法用于求解带容量约束的配送中心选址模型。仿真实验结果表明，此改进算法提高了最优解的求解精度与收敛速度。

英文摘要：

The traditional Median-based location model is expanded to build a capacitated location model, and a novel computa- tional method is developed. To avoid algorithm premature, a heterogeneous multi-swarm Particle Swarm Optimization （PSO） is proposed, in which the population consists of the master swarm and several sub-swarms with varying population structure to bet- ter balance exploitation and exploration abilities. A hybrid parallel encoding method is designed, and the improved algorithm is used to solve the capacitated location model. The experimental results demonstrate that the proposed algorithm enhances solu- tion accuracy and convergence speed.