Abstract: Using the artificial fish swarm algorithm which is improved by bacterial foraging algorithm, a new algorithm for solving the problem of distribution center location problem is presented. Approved artificial fish swarm algorithm based on bacterial foraging algorithm which has characteristics of local search ability of bacterial foraging algorithm is mainly aimed at the shortcomings of the basic artificial fish swarm algorithm to fall into local optimum. In the paper, the idea of chemotaxis in bacteria foraging algorithm is applied to the basic artificial fish swarm algorithm. Through the test of the algorithm, it can be seen that the improved artificial fish swarm algorithm is more effective than the basic fish swarm algorithm in search accuracy, reliability, optimization speed and stability. Through the simulation of the location, the improved artificial fish swarm algorithm is better than the basic fish swarm algorithm in solving the distribution center location problem, and lower costs can be found by improved artificial fish swarm algorithm.

Key words: distribution center location, artificial fish swarm algorithm, bacterial foraging, chemotaxis

摘要： 以细菌觅食算法改进的人工鱼群算法为工具，提出了一种新的解决配送中心选址问题的群智能算法。细菌觅食算法改进的人工鱼群算法主要针对基本人工鱼群算法后期容易陷入局部最优的缺点，利用细菌觅食算法局部搜索能力强的特点，将细菌觅食算法中的趋化思想应用到基本人工鱼群算法中。通过算法测试可以看出，改进人工鱼群算法在搜索精度、可靠性、优化速度及稳定性方面相对于基本鱼群算法更有效。通过选址实例仿真可以看出，改进人工鱼群算法在解决配送中心选址问题上相对于基本鱼群算法更具优越性，改进人工鱼群算法能够寻找到更低的成本。

关键词: 配送中心选址, 人工鱼群算法, 细菌觅食, 趋化