- WP1: New Models for Robust and Online Planning
The main aim of this WP is to initiate and explore entirely new modelling and algorithmic approaches in the broad areas of very large-scale robust and online optimization, distilling and generalizing the inherent mathematical and algorithmic ideas arising in the overall project. We proceed in three interdependent stages with increasing level of scientific challenge, innovation, and risk:
- In the robust planning stage, we critically reconsider the full planning process under the perspective of robust and online optimization.
- In the integrated planning stage, so far separately considered problems are simultaneously approached and integrated.
- In the new models stage, new computational and combinatorial models for robust and online planning of large-scale systems are developed.
- WP2: Robust Network and Line Planning
The main goal in this WP is to design robust network and line plans under customer-oriented or cost-oriented objectives. In particular, we aim at:
- Investigating the theoretical foundations of robust line planning through game theoretic approaches and under different stochastic scenarios of delays.
- Designing network and line plans that are robust to fluctuating customer demands and QoS prices in a way that the demand is satisfied without wasting resources.
- Understanding the specific structure of robust and line planning optimization problems that can be described as linear or nonlinear programs with a huge number of variables, and to develop efficient approximate solutions with guaranteed quality through novel relaxation techniques.
- WP3: Robust and Online Timetabling and Timetable Information Updating
This WP addresses the design of robust timetables and their online update. In particular, we aim at:
- Developing new and sophisticated modelling and solution strategies for robust and online timetable planning in a sound mathematical programming and computer science context.
- Understanding the interaction between robust and online timetable planning, and consider online requirements in the design of robust plans.
- Understanding better the structure of Mixed-Integer Programming (MIP) models for robust and online timetabling and their implications in the design of effective (exact/approximate) solution algorithms.
- Applying stochasticity in timetable models and monitoring the status quo of the system.
- Designing fast and efficient algorithms (and data structures) for online timetable adjustment after major disruptions, and for a reactive updating of the timetable information systems.
- WP4: Robust and Online Resource Scheduling
The objectives of this WP are the development of:
- Fast algorithmic methods for supporting robust scheduling and online rescheduling of railway rolling stock and crew, including shunting. These methods should provide solutions that have a high quality in an acceptable amount of time.
- A sound definition of robustness, as well as a conceptual framework for evaluating the results obtained from the algorithmic methods, in particular the online algorithmic methods.
- A conceptual framework for the collection of online data to monitor the status quo of the railway system.
- WP5: Delay Management
The goal of this WP is to address “delay management”, i.e., the passenger oriented immediate reaction of a railway system to small disturbances. In particular, we plan to:
- Address the multitude of operational delay management constraints efficiently.
- Consider delay management as a stochastic online problem.
- Investigate the interplay of short term delay management decisions with long term strategic planning,aiming at a suitable notion of robustness.
- WP6: Experimental Evaluation and Validation
The aim of this workpackage is:
- To provide prototype implementations for problems tackled in the other WPs and to perform experimental evaluations of the performance of the various implementations.
- To provide a systematic collection of test data for evaluating these implementations. These data involve important synthetic cases that will serve as benchmarks, as well as acquiring real-world data from railway companies.
- An additional goal of this workpackage is to evaluate and validate new approaches in existing simulation tools of railway companies.