@article{Karbstein, author = {Karbstein, Marika}, title = {Ohne Umsteigen ans Ziel}, series = {OR News}, volume = {52}, journal = {OR News}, pages = {12 -- 14}, abstract = {Die Anforderungen an das Liniennetz eines Verkehrsunternehmens sind vielf{\"a}ltig: kurze Fahrzeiten, viele Direktverbindungen und geringe Kosten. Mathematische Optimierungsmethoden k{\"o}nnen die Planung von Liniennetzen unterst{\"u}tzen und beste Kompromisse bzgl. aller Anforderungen berechnen.}, language = {de} } @phdthesis{Karbstein, author = {Karbstein, Marika}, title = {Line Planning and Connectivity}, isbn = {978-3-8439-1062-0}, abstract = {This thesis introduces the Steiner connectivity problem. It is a generalization of the well known Steiner tree problem. Given a graph G = (V, E) and a subset T ⊆ V of the nodes, the Steiner tree problem consists in finding a cost minimal set of edges connecting all nodes in T . The Steiner connectivity problem chooses, instead of edges, from a given set of paths a subset to connect all nodes in T . We show in the first part of this thesis that main results about complexity, approximation, integer programming formulations, and polyhedra can be generalized from the Steiner tree problem to the Steiner connectivity problem. An example for a straightforward generalization are the Steiner partition inequalities, a fundamental class of facet defining inequalities for the Steiner tree problem. They can be defined for the Steiner connectivity problem in an analogous way as for the Steiner tree problem. An example for a generalization that needs more effort is the definition of a directed cut formulation and the proof that this dominates the canonical undirected cut formulation enriched by all Steiner partition inequalities. For the Steiner connectivity problem this directed cut formulation leads to extended formulations, a concept that is not necessary for the Steiner tree problem. There are also major differences between both problems. For instance, the case T = V for the Steiner connectivity problem is equivalent to a set covering problem and, hence, not a polynomial solvable case as in the Steiner tree problem. The Steiner connectivity problem is not only an interesting generalization of the Steiner tree problem but also the underlying connectivity problem in line planning with inte- grated passenger routing. The integrated line planning and passenger routing problem is an important planning problem in service design of public transport and the topic of the second part. Given is the infrastructure network of a public transport system where the edges correspond to streets and tracks and the nodes correspond to stations/stops of lines. The task is to find paths in the infrastructure network for lines and passengers such that the capacities of the lines suffice to transport all passengers. Existing models in the literature that integrate a passenger routing in line planning either treat transfers in a rudimentary way and, hence, neglect an important aspect for the choice of the pas- senger routes, or they treat transfers in a too comprehensive way and cannot be solved for large scale real world problems. We propose a new model that focuses on direct connections. The attractiveness of transfer free connections is increased by introducing a transfer penalty for each non-direct connection. In this way, a passenger routing is computed that favors direct connections. For the computation of this model we also implemented algorithms influenced by the results for the Steiner connectivity problem. We can compute with our model good solutions that minimize a weighted sum of line operating costs and passengers travel times. These solutions improve the solutions of an existing approach, that does not consider direct connections, by up to 17\%. In contrast to a comprehensive approach, that considers every transfer and for which we could not even solve the root LP within 10 hours for large instances, the solutions of the new model, computed in the same time, are close to optimality (<1\%) or even optimal for real world instances. In a project with the Verkehr in Potsdam GmbH to compute the line plan for 2010 we showed that our approach is applicable in practice and can be used to solve real world problems.}, language = {en} } @inproceedings{Karbstein, author = {Karbstein, Marika}, title = {Integrated Line Planning and Passenger Routing: Connectivity and Transfers}, series = {Operations Research Proceedings 2014}, booktitle = {Operations Research Proceedings 2014}, doi = {10.1007/978-3-319-28697-6_37}, pages = {263 -- 269}, abstract = {The integrated line planning and passenger routing problem is an important planning problem in service design of public transport. A major challenge is the treatment of transfers. A main property of a line system is its connectivity. In this paper we show that analysing the connecvitiy aspect of a line plan gives a new idea to handle the transfer aspect of the line planning problem.}, language = {en} } @misc{Karbstein, author = {Karbstein, Marika}, title = {Integrated Line Planning and Passenger Routing: Connectivity and Transfers}, issn = {1438-0064}, doi = {10.1007/978-3-319-28697-6_37}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-52986}, abstract = {The integrated line planning and passenger routing problem is an important planning problem in service design of public transport. A major challenge is the treatment of transfers. A main property of a line system is its connectivity. In this paper we show that analysing the connecvitiy aspect of a line plan gives a new idea to handle the transfer aspect of the line planning problem.}, language = {en} } @article{BorndoerferKarbsteinPfetsch, author = {Bornd{\"o}rfer, Ralf and Karbstein, Marika and Pfetsch, Marc}, title = {The Steiner connectivity problem}, series = {Mathematical Programming A}, volume = {142}, journal = {Mathematical Programming A}, number = {1}, doi = {10.1007/s10107-012-0564-5}, pages = {133 -- 167}, language = {en} } @article{BorndoerferKarbsteinPfetsch, author = {Bornd{\"o}rfer, Ralf and Karbstein, Marika and Pfetsch, Marc}, title = {Models for Fare Planning in Public Transport}, series = {Discrete Applied Mathematics}, volume = {160}, journal = {Discrete Applied Mathematics}, number = {18}, doi = {10.1016/j.dam.2012.02.027}, pages = {2591 -- 2605}, language = {en} } @misc{BorndoerferKarbsteinMehrgardtetal., author = {Bornd{\"o}rfer, Ralf and Karbstein, Marika and Mehrgardt, Julika and Reuther, Markus and Schlechte, Thomas}, title = {The Cycle Embedding Problem}, issn = {1438-0064}, doi = {10.1007/978-3-319-28697-6_65}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-52788}, abstract = {Given two hypergraphs, representing a fine and a coarse "layer", and a cycle cover of the nodes of the coarse layer, the cycle embedding problem (CEP) asks for an embedding of the coarse cycles into the fine layer. The CEP is NP-hard for general hypergraphs, but it can be solved in polynomial time for graphs. We propose an integer rogramming formulation for the CEP that provides a complete escription of the CEP polytope for the graphical case. The CEP comes up in railway vehicle rotation scheduling. We present computational results for problem instances of DB Fernverkehr AG that justify a sequential coarse-first-fine-second planning approach.}, language = {en} } @inproceedings{BorndoerferKarbsteinMehrgahrdtetal., author = {Bornd{\"o}rfer, Ralf and Karbstein, Marika and Mehrgahrdt, Julika and Reuther, Markus and Schlechte, Thomas}, title = {The Cycle Embedding Problem}, series = {Operations Research Proceedings 2014}, booktitle = {Operations Research Proceedings 2014}, doi = {10.1007/978-3-319-28697-6_65}, pages = {465 -- 472}, abstract = {Given two hypergraphs, representing a fine and a coarse "layer", and a cycle cover of the nodes of the coarse layer, the cycle embedding problem (CEP) asks for an embedding of the coarse cycles into the fine layer. The CEP is NP-hard for general hypergraphs, but it can be solved in polynomial time for graphs. We propose an integer rogramming formulation for the CEP that provides a complete escription of the CEP polytope for the graphical case. The CEP comes up in railway vehicle rotation scheduling. We present computational results for problem instances of DB Fernverkehr AG that justify a sequential coarse-first-fine-second planning approach.}, language = {en} } @inproceedings{BorndoerferKarbsteinLiebchenetal., author = {Bornd{\"o}rfer, Ralf and Karbstein, Marika and Liebchen, Christian and Lindner, Niels}, title = {A Simple Way to Compute the Number of Vehicles That Are Required to Operate a Periodic Timetable}, series = {18th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2018)}, volume = {65}, booktitle = {18th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2018)}, doi = {10.4230/OASIcs.ATMOS.2018.16}, pages = {16:1 -- 16:15}, abstract = {We consider the following planning problem in public transportation: Given a periodic timetable, how many vehicles are required to operate it? In [9], for this sequential approach, it is proposed to first expand the periodic timetable over time, and then answer the above question by solving a flow-based aperiodic optimization problem. In this contribution we propose to keep the compact periodic representation of the timetable and simply solve a particular perfect matching problem. For practical networks, it is very much likely that the matching problem decomposes into several connected components. Our key observation is that there is no need to change any turnaround decision for the vehicles of a line during the day, as long as the timetable stays exactly the same.}, language = {en} } @misc{BorndoerferKarbsteinLiebchenetal., author = {Bornd{\"o}rfer, Ralf and Karbstein, Marika and Liebchen, Christian and Lindner, Niels}, title = {A Simple Way to Compute the Number of Vehicles That Are Required to Operate a Periodic Timetable}, issn = {1438-0064}, doi = {10.4230/OASIcs.ATMOS.2018.16}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-69688}, abstract = {We consider the following planning problem in public transportation: Given a periodic timetable, how many vehicles are required to operate it? In [9], for this sequential approach, it is proposed to first expand the periodic timetable over time, and then answer the above question by solving a flow-based aperiodic optimization problem. In this contribution we propose to keep the compact periodic representation of the timetable and simply solve a particular perfect matching problem. For practical networks, it is very much likely that the matching problem decomposes into several connected components. Our key observation is that there is no need to change any turnaround decision for the vehicles of a line during the day, as long as the timetable stays exactly the same.}, language = {en} }