基于群体智能优化算法的物资配送数学模型研究

Research on mathematical model of material distribution based on swarm intelligence optimization algorithm

为提供物资配送性能,采用群体智能算法用于物资配送数学模型优化,以降低物资配送成本。首先提出物资配送问题模型,选择物资配送中心所有商品配送至各配送点的成本总和作为优化目标函数,然后采用灰狼算法进行优化,将配送中心与配送点坐标映射至狼群分布坐标,采用配送成本总和的倒数作为适应度函数,选择3个最优个体作为高级狼,剩余为普通狼,普通狼不断的位置更新跟随高级狼,最后获得适应度最高的跟随路径即为物资配送路径。实验证明:通过灰狼优化的物资配送路径,相比于常用的物资配送路径规划算法,能够获得更低的配送成本。

In order to provide the performance of material distribution,swarm intelligence algorithm was used to optimize the mathematical model of material distribution to reduce the cost of material distribution.Firstly,a material distribution problem model was proposed.The cost sum of all goods delivered to each distribution point in the material distribution center was selected as the optimization objective function.Then,the gray wolf algorithm was used to optimize.The coordinates of distribution center and distribution point were mapped to the distribution coordinates of wolves.The reciprocal of the sum of distribution cost was used as the fitness function.Three optimal individuals were selected as senior wolves,and the rest was common Through the wolf,the ordinary wolf constantly updated the position to follow the senior wolf,and finally obtained the highest fitness following path,that was the material distribution path.Experimental results showed that the material distribution path optimized by gray wolf can obtain lower distribution cost compared with the commonly used material distribution path planning algorithm.