Look-Ahead Approaches for Integrated Planning in Public Transportation

In this paper we deal with three consecutive planning stages in public transportation: Line planning (including line pool generation), timetabling, and vehicle scheduling. These three steps are traditionally performed one after another in a sequential way often leading to high costs in the (last) vehicle scheduling stage. In this paper we propose three different ways to "look ahead", i.e., to include aspects of vehicle scheduling already earlier in the sequential process: an adapted line pool generation algorithm, a new cost structure for line planning, and a reordering of the sequential planning stages. We analyze these enhancements experimentally and show that they can be used to decrease the costs significantly

A New Sequential Approach to Periodic Vehicle Scheduling and Timetabling

When evaluating the operational costs of a public transport system, the most important factor is the number of vehicles needed for operation. In contrast to the canonical sequential approach of first fixing a timetable and then adding a vehicle schedule, we consider a sequential approach where a vehicle schedule is determined for a given line plan and only afterwards a timetable is fixed. We compare this new sequential approach to a model that integrates both steps. To represent various operational requirements, we consider multiple possibilities to restrict the vehicle circulations to be short, as this can provide operational benefits. The sequential approach can efficiently determine public transport plans with a low number of vehicles. This is evaluated theoretically and empirically demonstrated for two close-to real-world instances

Towards Improved Robustness of Public Transport by a Machine-Learned Oracle

The design and optimization of public transport systems is a highly complex and challenging process. Here, we focus on the trade-off between two criteria which shall make the transport system attractive for passengers: their travel time and the robustness of the system. The latter is time-consuming to evaluate. A passenger-based evaluation of robustness requires a performance simulation with respect to a large number of possible delay scenarios, making this step computationally very expensive. For optimizing the robustness, we hence apply a machine-learned oracle from previous work which approximates the robustness of a public transport system. We apply this oracle to bi-criteria optimization of integrated public transport planning (timetabling and vehicle scheduling) in two ways: First, we explore a local search based framework studying several variants of neighborhoods. Second, we evaluate a genetic algorithm. Computational experiments with artificial and close to real-word benchmark datasets yield promising results. In all cases, an existing pool of solutions (i.e., public transport plans) can be significantly improved by finding a number of new non-dominated solutions, providing better and different trade-offs between robustness and travel time

Cost-Minimal Public Transport Planning

In this paper we discuss what a cost-optimal public transport plan looks like, i.e., we determine a line plan, a timetable and a vehicle schedule which can be operated with minimal costs while, at the same time, allowing all passengers to travel between their origins and destinations. We are hereby interested in an exact solution of the integrated problem. In contrast to a passenger-optimal transport plan, in which there is a direct connection for every origin-destination pair, the structure or model for determining a cost-optimal transport plan is not obvious and has not been researched so far. We present three models which differ with respect to the structures we are looking for. If lines are directed and may contain circles, we prove that a cost-optimal schedule can (under weak assumptions) already be obtained by first distributing the passengers in a cost-optimal way. We are able to streamline the resulting integer program such that it can be applied to real-world instances. The model gives bounds for the general case. In the second model we look for lines operated in both directions, but allow only simplified vehicle schedules. This model then yields stronger bounds than the first one. Our most realistic model looks for lines operated in both directions, and allows all structures for the vehicle schedules. This model, however, is only computable for small instances. Finally, the results of the three models and their respective bounds are compared experimentally

Does a Simple Lattice Protein Folding Model Exhibit Self-Organized Criticality?

Proteins are known to fold into tertiary structures that determine their functionality in living organisms. However, the way they consistently fold to the same structure is unknown. Our research sees if the folding process can be viewed computationally through the lens of self-organized criticality using a simple lattice-bound protein

Sustainability ratings of defense companies and arms exports to war zones

This thesis analyzes whether ESG scores differ between companies that export arms to war zones and companies that do not, and whether the ESG scores of companies that export more weapons to more war zones differ from companies with fewer exports to fewer war zones. The findings indicate that common ESG ratings assessing financial sustainability risks relative to peer industries tend to be positively related to arms exports to war zones. Large discrepancies are found between the expectations of consumers about ESG ratings and the actual approaches of these ratings

Quality Control Factors Influencing the Successful and Reliable Implementation of Oocyte and Embryo Vitrification

Clinical vitrification evolved slowly, with interests and acceptance being commercially driven by the development of unique devices, safer solutions, and the misconception that ultra‐rapid cooling in an “open” system was a necessity to optimizing vitrification success. Furthermore, the dogma surrounding the importance of cooling rates has led to unsafe practices subject to excessive technical variation and risky modifications to create closed‐storage devices. The aim of this chapter is to highlight important quality control factors (e.g., ease of use, repeatability, reliability, labeling security, and cryostorage safety) into the selection process of which device/solution to use, independent of commercial manipulations. In addition, we provide clinical and experimental evidence in support of warming rates being the most important factor determining vitrification survival. Lastly, we exhibit indisputable support that aseptic, closed vitrification systems, specifically microSecure vitrification (μS‐VTF), can achieve success with attention to quality control details often lacking in open vitrification devices

Robustness Tests for Public Transport Planning

The classical planning process in public transport planning focuses on the two criteria operating costs and quality for passengers. Quality mostly considers quantities like average travel time and number of transfers. Since public transport often suffers from delays caused by random disturbances, we are interested in adding a third dimension: robustness. We propose passenger-oriented robustness indicators for public transport networks and timetables. These robustness indicators are evaluated for several public transport plans which have been created for an artificial urban network with the same demand. The study shows that these indicators are suitable to measure the robustness of a line plan and a timetable. We explore different trade-offs between operating costs, quality (average travel time of passengers), and robustness against delays. Our results show that the proposed robustness indicators give reasonable results