Abstract This paper addresses a vehicle routing problem with cross-docking (VRPCD) that considers truck scheduling, splitting pickup and delivery orders with time-windows at supplier and retailer locations, while optimizing two conflicting objectives (i.e., cost efficiency and responsiveness). The objectives are to minimize the total operational cost and the sum of the maximum earliness and tardiness. A new bi-objective mixed-integer linear programming model is presented and a multi-objective meta-heuristic evolutionary algorithm is proposed for solving the problem. Numerical results indicate the effectiveness of our proposed algorithm comparing with two multi-objective meta-heuristic algorithms (i.e., non-dominated sorting genetic algorithm (NSGA-II) and Pareto archived evolution strategy (PAES)). Also, we report findings from a hypothetical case study in a retail chain in Houston, Texas.

中文翻译：

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一个新的具有交叉对接的双目标车辆路线调度问题：数学模型和算法

摘要 本文解决了具有交叉配送 (VRPCD) 的车辆路径问题，该问题考虑了卡车调度、在供应商和零售商位置的时间窗口拆分取货和交货订单，同时优化了两个相互冲突的目标（即成本效率和响应能力）。目标是最小化总运营成本以及最大提前和延迟的总和。提出了一种新的双目标混合整数线性规划模型，并针对该问题提出了一种多目标元启发式进化算法。数值结果表明我们提出的算法与两种多目标元启发式算法（即非支配排序遗传算法（NSGA-II）和帕累托存档进化策略（PAES））相比的有效性。还，