现代物流信息管理中配送车辆路线优化研究

Optimization of Modern Logistics Distribution Routing

在分析车辆路线问题(VRP)现有启发式算法的基础上,提出了求解该问题的一种改进遗传算法(IGA)。该方法的核心在于针对遗传算法的局部搜索能力的不足,在选择、交叉、变异等遗传操作之后,引入逆转换位算子,根据适应度是否增加,对新产生的染色体进行多次逆转操作。模拟计算结果表明,该改进遗传算法明显增强了群体演化的质量,提高了算法收敛速度。

Based on the analysis of the existing heuristic algorithm for the vehicle routing problem（ VRP）, an improved genetic algorithm（IGA） is presented for the solution of this problem. The core of IGA is the construction of inversion operator, which overcomes the weakness of genetic algorithm and local search algorithm. Computational results demonstrate that IGA has great robustness for VRP and effectively raises the speed of convergence.