基于交通流的多模糊时间窗车辆路径优化

Vehicle Routing Problem with Multiple Fuzzy Time Windows Based on Traffic Flow

研究了基于交通流的多模糊时间窗车辆路径问题,考虑了实际中不断变化的交通流以及客户具有多个模糊时间窗的情况,以最小化配送总成本和最大化客户满意度为目标,构建基于交通流的多模糊时间窗车辆路径模型。根据伊藤算法的基本原理,设计了求解该模型的改进伊藤算法,结合仿真算例进行了模拟计算,并与蚁群算法的计算结果进行了对比分析,结果表明,利用改进伊藤算法求解基于交通流的多模糊时间窗车辆路径问题,迭代次数小,效率更高,能够在较短的时间内收敛到全局最优解,可以有效的求解多模糊时间窗车辆路径问题。

A multi-fuzzy time window vehicle routing problem based on traffic flow is investigated in this paper. The dynamic Change of traffic flow and the fuzzy time window of customers are considered. A multi-fuzzy time window vehicle routing model based on time-varying traffic flow is proposed, and the objective function is to minimize the total cost of distribution and maximize customer satisfaction. According to the basic principle of Ito algorithm, an improved Ito algorithm for solving the model is designed. We further do simulation on an example, and compare the results obtained byIto algorithm and ant colony algorithm. The results show that the improved ho algorithm to solve multi-fuzzy time window vehicle routing problem based on traffic flow has the advantages of small number of iterations and high efficiency, and it can converge to the global optimal solution in a short time. The improved Ito algorithm is an efficient algorithm for solving vehicle routing problem with multiple fuzzy time windows.