基于Hopfield神经网络算法的航线优化研究

Shipping route optimization based on Hopfield neural network algorithm

采用连续型Hopfield神经网络算法航线进行优化设计,综合考虑航线运价以及路程作的约束条件,设计最优航线。考虑构造相应置换矩阵,将目标函数以及约束条件作为构造条件设计相对应的能量函数,将问题的最优解映射到神经网络的稳定状态上,采用MATLAB软件进行算法的编程和求解,最终得出单位路程运价最低的航线优化方案。

The continuous Hopfield neural network algorithm is adopted to optimize the shipping route,taking both freight rate and distance into account to find optimization shipping route. Considering the corresponding displacement matrix,the objective function and the constraint condition are used as the corresponding condition structure energy function. The optimal solution of the problem is mapped to the steady state of the neural network. The research gained a lowest per-unit path tariff optimization with MATLAB,which provides a new insight into the refrigerated transport route planning.