eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Open Access Series in Informatics
2190-6807
2014-09-19
42
0
0
10.4230/OASIcs.ATMOS.2014
article
OASIcs, Volume 42, ATMOS'14, Complete Volume
Funke, Stefan
Mihalák, Matúš
OASIcs, Volume 42, ATMOS'14, Complete Volume
https://drops.dagstuhl.de/storage/01oasics/oasics-vol042-atmos2014/OASIcs.ATMOS.2014/OASIcs.ATMOS.2014.pdf
Analysis of Algorithms and Problem Complexity, Optimization, Combinatorics, Graph Theory, Applications
eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Open Access Series in Informatics
2190-6807
2014-09-19
42
i
ix
10.4230/OASIcs.ATMOS.2014.i
article
Frontmatter, Table of Contents, Preface, Workshop Organization
Funke, Stefan
Mihalák, Matús
Frontmatter, Table of Contents, Preface, Workshop Organization
https://drops.dagstuhl.de/storage/01oasics/oasics-vol042-atmos2014/OASIcs.ATMOS.2014.i/OASIcs.ATMOS.2014.i.pdf
Frontmatter
Table of Contents
Preface
Workshop Organization
eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Open Access Series in Informatics
2190-6807
2014-09-19
42
1
14
10.4230/OASIcs.ATMOS.2014.1
article
Delay-Robust Journeys in Timetable Networks with Minimum Expected Arrival Time
Dibbelt, Julian
Strasser, Ben
Wagner, Dorothea
We study the problem of computing delay-robust routes in timetable
networks. Instead of a single path we compute a decision graph containing all stops and trains/vehicles that might be relevant. Delays are formalized using a stochastic model. We show how to compute a decision graph that minimizes the expected arrival time while bounding the latest arrival time over all sub-paths. Finally we show how the information contained within a decision graph can compactly be represented to the user. We experimentally evaluate our algorithms and show that the running times allow for interactive usage on a realistic train network.
https://drops.dagstuhl.de/storage/01oasics/oasics-vol042-atmos2014/OASIcs.ATMOS.2014.1/OASIcs.ATMOS.2014.1.pdf
Algorithms
Optimization
Delay-robustness
Route planning
Public transportation
eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Open Access Series in Informatics
2190-6807
2014-09-19
42
15
24
10.4230/OASIcs.ATMOS.2014.15
article
Shortest Path with Alternatives for Uniform Arrival Times: Algorithms and Experiments
Nonner, Tim
Laumanns, Marco
The Shortest Path with Alternatives (SPA) policy differs from classical shortest path routing in the following way: instead of providing an exact list of means of transportation to follow, this policy gives such a list for each stop, and the traveler is supposed to pick the first option from this list when waiting at some stop. First, we show that an optimal policy of this type can be computed in polynomial time for uniform arrival times under reasonable assumptions. A similar result was so far only known for Poisson arrival times, which are less realistic for frequency-based public transportation systems. Second, we experimentally evaluate such policies. In this context, our main finding is that SPA policies are surprisingly competitive compared to traditional shortest paths, and moreover yield a significant reduction of waiting times, and therefore improvement of user experience, compared to similar greedy approaches. Specifically, for roughly 25% of considered cases, we could decrease the expected waiting time by at least 20%. To run our experiments, we also describe a tool-chain to derive the necessary information from the popular GTFS-format, therefore allowing the application of SPA policies to a wide range of public transportation systems.
https://drops.dagstuhl.de/storage/01oasics/oasics-vol042-atmos2014/OASIcs.ATMOS.2014.15/OASIcs.ATMOS.2014.15.pdf
Shortest Path
Stochastic Optimization
Public Transportation
eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Open Access Series in Informatics
2190-6807
2014-09-19
42
25
33
10.4230/OASIcs.ATMOS.2014.25
article
Locating Battery Charging Stations to Facilitate Almost Shortest Paths
Arkin, Esther M.
Carmi, Paz
Katz, Matthew J.
Mitchell, Joseph S. B.
Segal, Michael
We study a facility location problem motivated by requirements pertaining to the distribution of charging stations for electric vehicles: Place a minimum number of battery charging stations at a subset of nodes of a network, so that battery-powered electric vehicles will be able to move between destinations using "t-spanning" routes, of lengths within a factor t > 1 of the length of a shortest path, while having sufficient charging stations along the way. We give constant-factor approximation algorithms for minimizing the number of charging stations, subject to the t-spanning constraint. We study two versions of the problem, one in which the stations are required to support a single ride (to a single destination), and one in which the stations are to support multiple rides through a sequence of destinations, where the destinations are revealed one at a time.
https://drops.dagstuhl.de/storage/01oasics/oasics-vol042-atmos2014/OASIcs.ATMOS.2014.25/OASIcs.ATMOS.2014.25.pdf
approximation algorithms; geometric spanners; transportation networks
eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Open Access Series in Informatics
2190-6807
2014-09-19
42
34
45
10.4230/OASIcs.ATMOS.2014.34
article
Online Train Shunting
Boeuf, Vianney
Meunier, Frédéric
At the occasion of ATMOS 2012, Tim Nonner and Alexander Souza defined a new train shunting problem that can roughly be described as follows. We are given a train visiting stations in a given order and cars located at some source stations. Each car has a target station. During the trip of the train, the cars are added to the train at their source stations and removed from it at their target stations. An addition or a removal of a car in the strict interior of the train incurs a cost higher than when the operation is performed at the end of the train. The problem consists in minimizing the total cost, and thus, at each source station of a car, the position the car takes in the train must be carefully decided. Among other results, Nonner and Souza showed that this problem is polynomially solvable by reducing the problem to the computation of a minimum independent set in a bipartite graph. They worked in the offline setting, i.e. the sources and the targets of all cars are known before the trip of the train starts. We study the online version of the problem, in which cars become known at their source stations. We derive a 2-competitive algorithm and prove than no better ratios are achievable. Other related questions are also addressed.
https://drops.dagstuhl.de/storage/01oasics/oasics-vol042-atmos2014/OASIcs.ATMOS.2014.34/OASIcs.ATMOS.2014.34.pdf
Bipartite graph
competitive analysis
online algorithm
train shunting problem
vertex cover
eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Open Access Series in Informatics
2190-6807
2014-09-19
42
46
61
10.4230/OASIcs.ATMOS.2014.46
article
Engineering Graph-Based Models for Dynamic Timetable Information Systems
Cionini, Alessio
D'Angelo, Gianlorenzo
D'Emidio, Mattia
Frigioni, Daniele
Giannakopoulou, Kalliopi
Paraskevopoulos, Andreas
Zaroliagis, Christos
Many efforts have been done in the last years to model public transport timetables in order to find optimal routes. The proposed models can be classified into two types: those representing the timetable as an array, and those representing it as a graph. The array-based models have been shown to be very effective in terms of query time, while the graph-based models usually answer queries by computing shortest paths, and hence they are suitable to be used in combination with speed-up techniques developed for road networks.
In this paper, we focus on the dynamic behavior of graph-based models considering the case where transportation systems are subject to delays with respect to the given timetable. We make three contributions: (i) we give a simplified and optimized update routine for the well-known time-expanded model along with an engineered query algorithm; (ii) we propose a new graph-based model tailored for handling dynamic updates; (iii) we assess the effectiveness of the proposed models and algorithms by an experimental study, which shows that both models require negligible update time and a query time which is comparable to that required by some array-based models.
https://drops.dagstuhl.de/storage/01oasics/oasics-vol042-atmos2014/OASIcs.ATMOS.2014.46/OASIcs.ATMOS.2014.46.pdf
Timetabling
dynamic updates
queries
shortest paths
eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Open Access Series in Informatics
2190-6807
2014-09-19
42
62
78
10.4230/OASIcs.ATMOS.2014.62
article
Local Search for the Resource Constrained Assignment Problem
Reuther, Markus
The resource constrained assignment problem (RCAP) is to find a minimal cost cycle partition in a directed graph such that a resource constraint is fulfilled. The RCAP has its roots in an application that deals with the covering of a railway timetable by rolling stock vehicles. Here, the resource constraint corresponds to maintenance constraints for rail vehicles. Moreover, the RCAP generalizes several variants of vehicle routing problems. We contribute a local search algorithm for this problem that is derived from an exact algorithm which is similar to the Hungarian method for the standard assignment problem. Our algorithm can be summarized as a k-OPT heuristic, exchanging k arcs of an alternating cycle of the incumbent solution in each improvement step. The alternating cycles are found by dual arguments from linear programming. We present computational results for instances from our railway application at Deutsche Bahn Fernverkehr AG as well as for instances of the vehicle routing problem from the literature.
https://drops.dagstuhl.de/storage/01oasics/oasics-vol042-atmos2014/OASIcs.ATMOS.2014.62/OASIcs.ATMOS.2014.62.pdf
Assignment Problem
Local Search
Rolling Stock Rotation Problem
Vehicle Routing Problem
eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Open Access Series in Informatics
2190-6807
2014-09-19
42
79
91
10.4230/OASIcs.ATMOS.2014.79
article
A Coarse-To-Fine Approach to the Railway Rolling Stock Rotation Problem
Borndörfer, Ralf
Reuther, Markus
Schlechte, Thomas
We propose a new coarse-to-fine approach to solve certain linear programs by column generation. The problems that we address contain layers corresponding to different levels of detail, i.e., coarse layers as well as fine layers. These layers are utilized to design efficient pricing rules. In a nutshell, the method shifts the pricing of a fine linear program to a coarse counterpart. In this way, major decisions are taken in the coarse layer, while minor details are tackled within the fine layer. We elucidate our methodology by an application to a complex railway rolling stock rotation problem. We provide comprehensive computational results that demonstrate the benefit of this new technique for the solution of large scale problems.
https://drops.dagstuhl.de/storage/01oasics/oasics-vol042-atmos2014/OASIcs.ATMOS.2014.79/OASIcs.ATMOS.2014.79.pdf
Coarse-To-Fine Linear Programming
Rolling Stock Rotation Problem
eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Open Access Series in Informatics
2190-6807
2014-09-19
42
92
106
10.4230/OASIcs.ATMOS.2014.92
article
Mathematical programming models for scheduling locks in sequence
Passchyn, Ward
Briskorn, Dirk
Spieksma, Frits C.R.
We investigate the scheduling of series of consecutive locks. This setting occurs naturally along canals and waterways. We describe a problem that generalizes different models that have been studied in literature. Our contribution is to (i) provide two distinct mathematical programming formulations, and compare them empirically, (ii) show how these models allow for minimizing emission by having the speed of a ship as a decision variable, (iii) to compare, on realistic instances, the optimum solution found by solving the models with the outcome of a decentralized heuristic.
https://drops.dagstuhl.de/storage/01oasics/oasics-vol042-atmos2014/OASIcs.ATMOS.2014.92/OASIcs.ATMOS.2014.92.pdf
Mixed Integer Programming
Inland Waterways
Lock Scheduling
eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Open Access Series in Informatics
2190-6807
2014-09-19
42
107
121
10.4230/OASIcs.ATMOS.2014.107
article
Simultaneous frequency and capacity setting for rapid transit systems with a competing mode and capacity constraints
De-Los-Santos, Alicia
Laporte, Gilbert
Mesa, Juan A.
Perea, Federico
The railway planning problem consists of several consecutive phases: network design, line planning, timetabling, personnel assignment and rolling stocks planning. In this paper we will focus on the line planning process. Traditionally, the line planning problem consists of determining a set of lines and their frequencies optimizing a certain objective. In this work we will focus on the line planning problem context taking into account aspects related to rolling stock and crew operating costs. We assume that the number of possible vehicles is limited, that is, the problem that we are considering is a capacitated problem and the line network can be a crowding network. The main novelty in this paper is the consideration of the size of vehicles and frequencies as variables as well as the inclusion of a congestion function measuring the level of in-vehicle crowding. Concretely, we present the problem and an algorithm to solve it, which are tested via a computational experience.
https://drops.dagstuhl.de/storage/01oasics/oasics-vol042-atmos2014/OASIcs.ATMOS.2014.107/OASIcs.ATMOS.2014.107.pdf
Line planning
railway
capacity
frequency
congestion
eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Open Access Series in Informatics
2190-6807
2014-09-19
42
122
137
10.4230/OASIcs.ATMOS.2014.122
article
Timing of Train Disposition: Towards Early Passenger Rerouting in Case of Delays
Lemnian, Martin
Rückert, Ralf
Rechner, Steffen
Blendinger, Christoph
Müller-Hannemann, Matthias
Passenger-friendly train disposition is a challenging, highly complex online optimization problem with uncertain and incomplete information about future delays. In this paper we focus on the timing within the disposition process. We introduce three different classification schemes to predict as early as possible the status of a transfer: whether it will almost surely break, is so critically delayed that it requires manual disposition, or can be regarded as only slightly uncertain or as being safe. The three approaches use lower bounds on travel times, historical distributions of delay data, and fuzzy logic, respectively. In experiments with real delay data we achieve an excellent classification rate. Furthermore, using realistic passenger flows we observe that there is a significant potential to reduce the passenger delay if an early rerouting strategy is applied.
https://drops.dagstuhl.de/storage/01oasics/oasics-vol042-atmos2014/OASIcs.ATMOS.2014.122/OASIcs.ATMOS.2014.122.pdf
train delays
event-activity model
timing of decisions
passenger flows
passenger rerouting
eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Open Access Series in Informatics
2190-6807
2014-09-19
42
138
151
10.4230/OASIcs.ATMOS.2014.138
article
Speed-Consumption Tradeoff for Electric Vehicle Route Planning
Baum, Moritz
Dibbelt, Julian
Hübschle-Schneider, Lorenz
Pajor, Thomas
Wagner, Dorothea
We study the problem of computing routes for electric vehicles (EVs) in road networks. Since their battery capacity is limited, and consumed energy per distance increases with velocity, driving the fastest route is often not desirable and may even be infeasible. On the other hand, the energy-optimal route may be too conservative in that it contains unnecessary detours or simply takes too long. In this work, we propose to use multicriteria optimization to obtain Pareto sets of routes that trade energy consumption for speed. In particular, we exploit the fact that the same road segment can be driven at different speeds within reasonable intervals. As a result, we are able to provide routes with low energy consumption that still follow major roads, such as freeways.
Unfortunately, the size of the resulting Pareto sets can be too large to be practical. We therefore also propose several nontrivial techniques that can be applied on-line at query time in order to speed up computation and filter insignificant solutions from the Pareto sets.
Our extensive experimental study, which uses a real-world energy consumption model, reveals that we are able to compute diverse sets of alternative routes on continental networks that closely resemble the exact Pareto set in just under a second---several orders of magnitude faster than the exhaustive algorithm.
https://drops.dagstuhl.de/storage/01oasics/oasics-vol042-atmos2014/OASIcs.ATMOS.2014.138/OASIcs.ATMOS.2014.138.pdf
electric vehicles
shortest paths
route planning
bicriteria optimization
algorithm engineering