Air cargo decision systems

为了在竞争中生存并保持领先地位，航空货运公司必须不断地对其运输网络的使用做出关键决策。从长远来看，他们必须就下个航季每个始发和目的地机场之间的航班班次和容量做出战略决定。另一方面，在中短期内，他们必须就如何利用他们的交通网络运输货物做出战术和作战上的选择。由于不确定性在航空货运业中无处不在，做出可能的最佳决策不仅需要良好的优化模型，还需要可靠的预测工具。 在业内，一些决策工具可用于支持货运航空公司的规划和运营。然而，由于涉及的问题的难度，这些工具的质量往往很差，从业者在就他们面临的一些最常见的问题做出选择时不能完全依赖它们。 该项目的主要目标是开发新的优化模型和基本预测工具，以应对航空货运业中仍存在挑战的某些方面的货运。我们会在不同的规划层面追求这些目标。在战略层面上，考虑到主要的竞争对手航空公司，我们将有兴趣评估一家航空公司提供的服务修改对其业务的影响。在战术层面，我们将研究如何利用定期重新优化发货计划来改善向货运订单分配路线的方式。最后，在运营层面，我们建议开发工具，使员工在为订单分配路线时能够做出更明智的决定。 这些新的优化和预测工具应该可以让我们的工业合作伙伴做出更好的规划决策，从而获得竞争优势。

In order to survive and stay ahead of the competition, airfreight carriers have to continuously make key decisions regarding the use of their transportation network. On the long-term horizon, they have to make strategic decisions about the frequency and the capacity of the flights between each of the origin and destination airports for the next season. On the other hand, on the mid- and short-term horizons, they have to make tactical and operational choices about how their transportation network will be used to transport the goods. Since uncertainty is omnipresent in the air cargo industry, making the best decisions possible requires not only good optimization models, but also reliable forecasting tools. In the industry, some decision-making tools are available to support cargo airlines in their planning and operations. However, due to the difficulty of the problems involved, the quality of these tools is often poor, and practitioners cannot fully rely on them when making choices concerning some of the most common problems they face. The main goal of this project is to develop new optimization models and the underlying forecasting tools to deal with certain aspects of freight transportation that still represent a challenge in the air cargo industry. We will pursue these objectives at different levels of planning. At the strategic level, we will be interested in evaluating the impact of a modification of the services offered by an airline company on its business, in consideration of the main competitor airlines. At the tactical level, we will examine how periodical reoptimization of the shipping plan can be used to improve the way routes are assigned to freight orders. Finally, at the operational level, we propose to develop tools that would allow employees to make a more informed decision when assigning a route to an order. These new optimization and forecasting tools should allow our industrial partner to make better planning decisions and, as a result, gain a competitive advantage.