# Learning-Based Optimisation for Integrated Problems in
## 2 Transport Planning Problems in IFT
### International Transport Operations
[PERSON] and [PERSON] [15] categorise the key planning processes in IFT from the operator's perspective and summarise them under three umbrellas: system design, service network design, and operational planning. In the following, we will briefly describe these three areas and add terminal operations planning as a fourth major area in IFT. System Design: This mainly encompasses the decisions of the shippers, receivers, freight forwarder, and the road operator regarding the infrastructure and asset planning. This includes network design, network flow planning, and service network design problems [16]. Stakeholders consider long-term planning decisions such as determining the number, capacity and location of terminals, long-term line planning, and assignment of supply and delivery regions. These decisions typically entail the procurements and allocation of physical resources and the selection of geographical locations, spanning a time horizon from several years to even decades [17]. System design models are used to evaluate and rank alternatives for such planning issues. Most of them are often aggregated, static, and deterministic, where the uncertainties are handled based on strategic forecasts within formulated scenarios [15; 18; 19]. The objectives in this phase are mostly generic, aiming to find the system optimum by minimising the total system cost. Service Design: Based on the results of the system design phase (i.e., fixed sites, infrastructure, and selection of dispatch/delivery zones, i.e., origin-destination), the freight forwarder plans its transport operations within the available resources and in accordance with the services provided by the rail and road operators. Thus, the main optimisation concern in this phase is to assign and redistribute resources across or within the intermodal network. Specifically, tactical service network design involves determining routes and frequencies, finding the schedule and selecting the modality for each corridor, and assigning transport services given the capacity in that corridor [20; 21]. IFT, which involves additional operations such as trans-shipment and consolidation, tends to be slower and less reliable than unimodal road transport, making scheduling with the objective of minimising delays crucial for intermodal networks [22; 23]. To operate effectively, decision-makers in this phase are highly dependent on mid-term predictions, such as demand and available resources. Some recent studies introduce stochastic models for service network design problems in order to tackle uncertainties in an integrated manner [24; 25]. Operational Planning: This domain includes the near- or real-time decisions of all IFT stakeholders, ensuring efficient use of resources at any given point in time [15]. On this level, the carriers are primarily focused on vehicle routing, fleet management, personnel scheduling, and resource allocation. The routine of the freight forwarders and rail operators consists of delay management and rescheduling the train operations, i.e., dispatching [22]. The road operator redistributes and moves vehicles within the road network. [PERSON] et al. [4] classify the operational planning problems in intermodal transport into Resource Management Problems and itinerary replanning. The former class deals with the distribution of the resources and includes problems such as empty loading unit repositioning and fleet management problems. The latter focuses on real-time optimisation of schedules, modal routes, and relevant responses to operational disturbances. Since uncertainties are frequent in operational planning, the solution models usually incorporate high stochasticity and the dynamics of the environment, considering detailed time frames. Terminal Operations: Terminal operations are highly integrated within service network design and encompass decisions regarding the assignment of resources (e.g., cranes) and sorting (e.g., loading units) under a given capacity and time constraints [15; 26].