Urbanization, a desire for a reduction of CO2 and a need for a more efficient use of space are likely to greatly increase demand for rail travel in the coming decades. To improve railway capacity, extra infrastructure can be built, or existing track can be optimized. A silo analogy provides an interesting idea for an integral approach to network development that combines the demand of heavy-rail and bus, tram, and metro: either obtain more demand for the heavy-rail system and thus validate expensive infrastructural investments or reduce demand. Both options require a broadening of the analysis so that it includes bus, tram, and metro networks. To explore the practical implications of this analogy, the research question is set up as follows: “Does integrated public transport network development in the form of a simultaneous consideration for infrastructural investment in both heavy-rail and hierarchically lower public transport modes offer a better solution for fulfilling transportation needs, compared to a segregated approach?” To answer the research question, literature review has been used to gain insights in public transport integration from a technical and a governance perspective. Literature has also been used to form integration strategies that could be applied in network development. The formed strategies consist of using network hierarchy as a guideline for either applying bus, tram, and metro to take over lower hierarchy services from the heavy-rail and vice versa. A case study on the corridor Amsterdam – Lelystad in The Netherlands was used to apply the integration strategies on and to analyze the effects of the development following the different strategies in a real-life situation. The results show that the variant following the strategy of assigning lower hierarchy services to heavy-rail appears best in terms of generalized travel time, synthetic demand, and investment costs. It scores well on fairness of the offer, but lowest on ambition fulfillment and operational costs. It turned out that each variant needed investment in more heavy-rail infrastructure to allow for completing of the heavy-rail ambitions. The variant with more tasks assigned to bus, tram, and metro scored the worst, except for ambition fulfillment. Furthermore, the multicriteria analysis, although useful for providing insights in the qualities of the different variants, does not give a definitive answer on what the best variant would be. Using external input to assign weights to the multicriteria analyses would have been a good improvement in getting to that answer. Instead, a stakeholder reflection is done to give insight in possible stances regarding the criteria from the stakeholder’s perspective. The research suggests that it is worth considering ambitions and problems outside of just the bus, tram, and metro or just the heavy-rail system. The process of brainstorming based on expertise, using qualitative multicriteria analyses for making decisions with supporting arguments in the design phase, planning a plausible timetable and analyzing and comparing several variants forms a good skeleton for investigating the possibilities of public transport network development in places where heavy-rail capacity becomes problematic.

The current research addresses a problem found in the area of railway operations regarding the maintenance of rolling stock units. It focuses on the situation in The Netherlands and approaches the problem from the perspective of its main railway operator N.V. Nederlandse Spoorwegen (NS). The increasing use of the capacity of the railway network leads to two issues. First, the complexity of the scheduling process is increasing, raising the need for tools that automate this process. Second, since NS is considering to perform more maintenance activities during daytime, raising the question at which locations maintenance teams needs to be stationed to perform daytime maintenance. These issues are interrelated. The model development in the current research, tackling the aforementioned issues, can be understood as a three-stage framework. Assuming a given rolling stock circulation, the first stage aims to find the maintenance schedule and maintenance location choice minimizing the total number of nighttime maintenance activities. The second stage introduces a model to compute the required capacity. The third stage integrates the first and second stage, aiming to find a solution to the first-stage model that satisfies some predetermined maintenance location capacity constraints that can be determined by the second-stage model. First, it is shown that, for a scenario with 20 maintenance locations for daytime maintenance, up to 42.0% of the work can be performed during daytime. Also, the second model can be used to efficiently (i.e. within seconds) compute required capacity and an accurate maintenance activity planning. Moreover, results for the third model have been generated showing, for example, that in one considered problem instance, the number of maintenance shifts for which the required capacity exceeds the available capacity can be reduced from 21 to 5 in 7.6 minutes. In addition to the aforementioned experimental results, a more practical approach is taken as well by constructing a small use case, demonstrating how the current research can be applied in practical situations. To this end, planning software Viriato is used, by which various visualizations of maintenance schedules can be provided.