The paper addresses the green sequencing and routing problem, which consists in determining the best sequence of locations to visit within a warehouse for storing and/or retrieval operations, using a fleet composed of both electric vehicles, e.g., equipped with a lithium-ion battery, and conventional vehicles, i.e., with an internal combustion engine. We present a Mixed-Integer Linear Programming formulation to the problem and propose two matheuristics based on suitable decompositions of the mathematical formulation. The two matheuristics have been tested on a pool of small-medium size instances and their performance has been compared to the one of a third matheuristic, previously proposed for the case of conventional vehicles only and here suitable extended to deal with the green aspects of the problem. The performed analysis allowed one to identify the most promising matheuristic in terms of some standard computational indicators, i.e., computing time and percentage optimality gap, as well as in terms of some qualitative aspects of the solutions agreed with a reference company. Such a most promising algorithm has then been further tested to gather some technical insights on what makes the problem hard to solve, as well as to outline some managerial insights. Moreover, its performance has been tested on a pool of real instances comprising ordinary days (with a usual amount of operations to perform) and extremely busy days, showing its efficacy and efficiency also in the considered real application context.

该论文解决了绿色排序和路由问题，其中包括使用由两辆电动汽车（例如配备锂离子电池）组成的车队，确定仓库内进行存储和/或检索操作的最佳位置访问顺序和传统车辆，即带有内燃机的车辆。我们针对该问题提出了混合整数线性规划公式，并基于数学公式的适当分解提出了两种数学方法。这两种数学方法已在一组中小型实例上进行了测试，并将其性能与第三种数学方法进行了比较，第三种数学方法之前仅针对传统车辆的情况提出，此处适合扩展以处理车辆的绿色方面。问题。所进行的分析使人们能够根据一些标准计算指标（即计算时间和百分比最优性差距）以及与参考公司达成一致的解决方案的一些定性方面来确定最有前途的数学方法。然后，对这种最有前途的算法进行了进一步测试，以收集一些有关问题难以解决的技术见解，并概述了一些管理见解。此外，它的性能已经在包括普通日子（需要执行通常数量的操作）和极其繁忙的日子的真实实例池上进行了测试，在考虑的真实应用程序环境中也显示了其功效和效率。以及与参考公司商定的解决方案的一些定性方面。然后，对这种最有前途的算法进行了进一步测试，以收集一些有关问题难以解决的技术见解，并概述了一些管理见解。此外，它的性能已经在包括普通日子（需要执行通常数量的操作）和极其繁忙的日子的真实实例池上进行了测试，在考虑的真实应用程序环境中也显示了其功效和效率。以及与参考公司商定的解决方案的一些定性方面。然后，对这种最有前途的算法进行了进一步测试，以收集一些有关问题难以解决的技术见解，并概述了一些管理见解。此外，它的性能已经在包括普通日子（需要执行通常数量的操作）和极其繁忙的日子的真实实例池上进行了测试，在考虑的真实应用程序环境中也显示了其功效和效率。