部分联合运输策略下的物流车辆路径优化问题研究

论文分析了物流车辆路径优化问题的特点,提出了企业自营物流和第三方物流协同运输的部分联合运输策略。根据客户需求节点的特点进行了节点分类,建立了以车辆调用成本、车辆运输成本、第三方物流运输成本之和最小为目标的整数线性规划模型。根据部分联合运输策略下各类客户需求点运输方式特点,构造了一种新的变维数矩阵编码结构,并对传统算法中概率选择操作方式进行修改,提出了一种新的智能优化算法并与枚举法和遗传算法的运算结果进行了算法性能对比分析。结果显示,本文提出的逆选择操作蚁群算法具有较快的运算速度和较高的稳定性,是求解此类问题的一种有效算法。

Research on Logistics Vehicle Routing Optimum Problems with Partial Combined Transport Strategy

We analyze the characteristic of logistics vehicle routing optimum problems, and propose a partial combined transport strategy of collaborative transportation with self-support logistics and third party logistic. Customer nodes are classified into certain types according to their characteristic of demand. An integer linear programming model is proposed,and the objective function is to minimize the total costs including the fixed costs of self-support vehicles , the transportation costs of self-support vehicles and the transportation costs of 3PL vehicles.Based on the transportation mode of the different customer nodes, an improved ACO algorithm by improving the coding mode and possible selection(ACO-nso)is proposed, and we compare the results obtained by ACO-nso algorithm , EA(enumeration method)method and GA( genetic algorithm) algorithm.It is shown that the model and ACO-nso algorithm improved in this paper require a shorter time of calculation and better global searching ability than traditional intelligent optimization algorithms. ACO-nso algorithm is an efficient algorithm for solving this kind of problem.