Problem instances for the hub-arrival-departure problem

We systematically generated problem instances for the hub-arrival-departure problem introduced in the article “Optimizing consolidation processes in hubs: The hub-arrival-departure problem. Working Paper Friedrich-Schiller-Universität Jena, 2020”. For a detailed description of the instance generation procedure, we would like to refer to Section 6.1 of the aforementioned article.

In order to evaluate the performance of our proposed solution methods, we generated 900 instances of HAD-MinLateShipments and 540 instances of HAD-MaxConsolidationTime which we provide in two separate datasets containing the respective instances as text files. Each instance is assigned a running index and is labeled as “_.txt”, with being either MLS (HAD-MinLateShipments) or MCT (HAD-MaxConsolidationTime) and with being the corresponding running index. Each file provides the same basic instance data: the number of vehicles \(n\), the set \(\Omega\) of vehicle paris \((i,j)\) exchanging goods among each other and the weight matrix \(w_{ij}\) indicating the number of shipments exchanged by vehicle pair \((i,j)\in \Omega\) . Additionally, for HAD-MinLateShipments, we provide the number of empty slots \(e\) as well as the consolidation time \(\delta\). Besides the basic parameter, we need to provide the number of allowed late shipments \(S\) for HAD-MaxConsolidationTime.

The text-files for HAD-MinLateShipments are structured as follows:

ID =

.

count_vehicles =

.

count_emptySlots =

.

delta =

.

omega =

.

weight =

.

The text-files for HAD-MaxConsolidationTime are structured as follows:

ID =

.

count_vehicles =

.

count_allowedMissedShipments =

.

omega =

.

weight =

.

In our article we also aim to evaluate the robustness of different objectives. Therefore, another 180 instances are generated. Naming convention as well as the structure of the text-files is in line with the previously introduced data-sets.

The text-files for simulation study are structured as follows:

ID =

.

count_vehicles =

.

count_emptySlots =

.

delta =

.

count_allowedMissedShipments =

.

omega =

.

weight =

.

本研究针对发表于《优化枢纽集拼流程：枢纽到达-出发问题》（2020年耶拿弗里德里希·席勒大学工作论文）的枢纽到达-出发问题（hub-arrival-departure problem），系统生成了该问题的标准化算例集。关于算例生成流程的详细说明，请参阅上述论文的第6.1节。

为验证本文提出的求解方法的性能，我们分别构建了900组HAD-MinLateShipments算例与540组HAD-MaxConsolidationTime算例，并将两类算例分别存储于两个独立的数据集中，所有算例均以纯文本文件形式提供。每个算例均配有唯一的运行索引，文件命名格式为"<标识前缀>_<运行索引>.txt"，其中<标识前缀>取值为MLS（对应HAD-MinLateShipments）或MCT（对应HAD-MaxConsolidationTime），<运行索引>为该算例的唯一编号。每个文本文件均包含以下基础算例数据：车辆总数(n)、表征两两车辆间货物交换关系的集合(Omega)（元素为车辆对((i,j))），以及表征车辆对((i,j)inOmega)之间交换货件数量的权重矩阵(w_{ij})。此外，针对HAD-MinLateShipments算例，我们额外提供了空槽位数(e)与集拼时长(delta)；针对HAD-MaxConsolidationTime算例，则需额外提供允许的延迟货件数(S)。

HAD-MinLateShipments的文本文件结构如下：
ID =
<算例编号>
count_vehicles =
<车辆总数>
count_emptySlots =
<可用空槽位数>
delta =
<集拼时长>
omega =
<车辆对集合>
weight =
<权重矩阵>

HAD-MaxConsolidationTime的文本文件结构如下：
ID =
<算例编号>
count_vehicles =
<车辆总数>
count_allowedMissedShipments =
<允许延迟货件数>
omega =
<车辆对集合>
weight =
<权重矩阵>

本研究同时旨在评估不同优化目标的鲁棒性，因此额外生成了180组测试算例。该类算例的命名规则与文本文件格式均与前述数据集保持一致。

仿真研究所用的文本文件结构如下：
ID =
<算例编号>
count_vehicles =
<车辆总数>
count_emptySlots =
<可用空槽位数>
delta =
<集拼时长>
count_allowedMissedShipments =
<允许延迟货件数>
omega =
<车辆对集合>
weight =
<权重矩阵>