SearcharxivSearch

arXiv subjects

Maximilian Viehauser

Publications and source records attributed to Maximilian Viehauser.

4 recordsLinked to original sources

Guided Exploration of Iterative Schedule Modifications: A Design Study on Railway Traction Unit Scheduling

Traction unit scheduling in large railway networks involves complex operational constraints: multi-objective optimization produces feasible circulation plans under ideal assumptions, while simulation is required to assess their robustness under realistic operating conditions. A critical refinement mechanism relies on crossing operations, in which co-located traction units exchange their remaining schedules to reduce delay propagation. The space of possible crossing sequences, however, grows exponentially. Existing tools provide limited support for identifying promising candidates, evaluating their impact, and managing the resulting exploration. We present an interactive visual exploration approach that tightly couples schedule visualization, simulation-based evaluation, and a three-level guidance mechanism to support the systematic exploration and interactive optimization of traction unit circulation plans. The system renders the circulation plan in its domain-familiar form and integrates simulation results to expose delay propagation directly within the planning context. A three-level guidance framework aggregates crossing candidates spatially and ranks them by estimated impact on key performance indicators (KPIs) at an overview level, while exposing detailed per-candidate evaluation at a detail level to support informed decision-making. Applying a crossing change triggers an automatic schedule recomputation and re-simulation, with a provenance-based history mechanism enabling the non-linear exploration of alternative modification paths. We demonstrate the approach through real-world use case scenarios and report substantial reductions in the time and effort required to identify and evaluate promising schedule modifications compared to the current workflow.

cs.HC

Novel Concepts for Agent-Based Population Modelling and Simulation: Updates from GEPOC ABM

In recent years, dynamic agent-based population models, which model every inhabitant of a country as a statistically representative agent, have been gaining in popularity for decision support. This is mainly due to their high degree of flexibility with respect to their area of application. GEPOC ABM is one of these models. Developed in 2015, it is now a well-established decision support tool and has been successfully applied for a wide range of population-level research questions ranging from health-care to logistics. At least in part, this success is attributable to continuous improvement and development of new methods. While some of these are very application- or implementation-specific, others can be well transferred to other population models. The focus of the present work lies on the presentation of three selected transferable innovations. We illustrate an innovative time-update concept for the individual agents, a co-simulation-inspired simulation strategy, and a strategy for accurate model parametrisation. We describe these methods in a reproducible manner, explain their advantages and provide ideas on how they can be transferred to other population models.

cs.MA

GEPOC Parameters -- Open Source Parametrisation and Validation for Austria, Version 2.0

GEPOC, short for Generic Population Concept, is a collection of models and methods for analysing population-level research questions. For the valid application of the models for a specific country or region, stable and reproducible data processes are necessary, which provide valid and ready-to-use model parameters. This work contains a complete description of the data-processing methods for computation of model parameters for Austria, based exclusively on freely and publicly accessible data. In addition to the description of the source data used, this includes all algorithms used for aggregation, disaggregation, fusion, cleansing or scaling of the data, as well as a description of the resulting parameter files. The document places particular emphasis on the computation of parameters for the most important GEPOC model, GEPOC ABM, a continuous-time agent-based population model. An extensive validation study using this particular model was made and is presented at the end of this work.

cs.AI

GEPOC ABM, Generic Population Concept -- Agent-Based Model, Version 2.2

The Generic Population Concept - Agent-Based Model, henceforth short, GEPOC ABM, is one of the models within GEPOC, a generic concept to model a country's population and its dynamics using causal modelling approaches. The model is well established and had already proven its worth in various use cases from evaluation of MMR vaccination rates to SARS-CoV-2 epidemics modelling. In this work we will reproducibly specify the base model, to be specific, version 2.2 of it, and several extensions. The base model GEPOC ABM depicts the population of a country with the features sex and age. It uses a co-simulation-inspired time-update, where person-level discrete-event simulators are synchronised by a simulation layer at macro-steps, making the approach amenable to parallelization. A core design choice is structuring person agents around the life-year rather than the calendar year; accordingly, each agent schedules demographic events annually on their birthday. To expand the model's capabilities beyond basic demographic features, GEPOC ABM Geography adds a residence feature in the form of geographical coordinates. Further extensions include GEPOC ABM IM, which adds internal migration processes in three variants, and GEPOC ABM CL, which models locations where agents may have contacts with each other. In this definition we solely specify the conceptual models and do not go into any details with respect to implementation or gathering/processing of parametrisation data.

q-bio.PE