Abstract: Aimed at the current situation of low loading rate of Less-than-Truck Load (LTL) logistics cargo,the cargo loading problem of multi-vehicle and multi-category cargo under limited cargo conditions was studied and a multi-objective mathematical model with the objectives of minimizing the number of vehicles and maximizing the total vehicle volume and total load utilization was constructed.Considering that a single piece of cargo added to a vehicle would have an impact on the remaining volume and remaining weight of that vehicle as well as the collection of vehicles,the dynamic volumetric-weight balance algorithm based on backtracking tree was designed,and the Pareto solution set was obtained by non-dominated sorting of the algorithm results,the congestion distance of each solution in the Pareto solution set was calculated,and the solution with the largest congestion distance was selected as the optimal loading solution.Finally,the algorithm was compared and analyzed with NSGA-2 and CPLEX in terms of computational accuracy and time complexity of the algorithm,and the results of the arithmetic examples verified the effectiveness of the proposed algorithm.

Key words: less-than-truckload logistic, cargo loading, multi-category, backtracking tree, dynamic volumetric-weight balance

摘要： 针对零担物流货物装载率低下的现状,研究货物有限条件下多车多品种货物的货物配载问题,构建以最小化车辆数量、最大化车辆总容积和总载重量利用率为目标的多目标数学模型,考虑到单件货物的装载会对车辆以及车辆集合的剩余容积和剩余载重量产生影响,设计基于动态容重比平衡法和装载回溯树的启发式算法,对算法结果进行非支配排序,得到帕累托解集,计算帕累托解集内每个解的拥挤距离,并选择拥挤距离最大的解为最优装载方案。以算法计算精度和时间复杂度为标准,将所设计算法与NSGA-2、CPLEX算法进行对比分析,算例结果验证了算法的有效性。

关键词: 零担物流, 货物配载, 多品种, 回溯树, 动态容重比平衡