Service Network Design with Packing Considerations

This thesis is part of a broader research project aimed at developing a mathematical model that integrates two NP-hard problems: the Service Network Design (SND) and the Bin Packing Problem (BPP). The goal is to analyse the economic and logistical benefits of such integration. The existing literature includes only a limited number of studies on the integration of the Scheduled Service Network Design (SSND) with the Bin Packing Problem (BPP), leaving a significant gap. Recent contributions have begun to explore the impact of demand loading rules on vehicles and packing constraints in intermodal transport (Kienzle et al., 2024; Morganti et al., 2020), as well as the challenges and advantages of integrating such constraints into network capacity planning (Bruni et al., 2023). However, crucial aspects such as revenue management and capacity selection in SSND remain underexplored. This study aims to bridge this gap by proposing a unified problem formulation that incorporates these elements, providing a framework applicable to contract negotiations and tactical planning in transportation and logistics systems. As part of this research project, the work carried out in this thesis represents a functional yet partial contribution. Specifically, realistic test scenarios were randomly generated while ensuring their compatibility with the corresponding network topology. Subsequently, computational experiments were conducted to examine the model’s behaviour across different scenarios, with a particular focus on two key parameters. The results obtained indicate promising effects in some cases, while in others, they suggest possible directions for future optimisations.