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Graph Partitioning with Natural Cuts
 In IPDPS. IEEE Computer Society
, 2011
"... Abstract. We present a novel approach to graph partitioning based on the notion of natural cuts. Our algorithm, called PUNCH, has two phases. The first phase performs a series of minimumcut computations to identify and contract dense regions of the graph. This reduces the graph size, but preserves ..."
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Cited by 24 (9 self)
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Abstract. We present a novel approach to graph partitioning based on the notion of natural cuts. Our algorithm, called PUNCH, has two phases. The first phase performs a series of minimumcut computations to identify and contract dense regions of the graph. This reduces the graph size, but preserves its general structure. The second phase uses a combination of greedy and local search heuristics to assemble the final partition. The algorithm performs especially well on road networks, which have an abundance of natural cuts (such as bridges, mountain passes, and ferries). In a few minutes, it obtains excellent partitions for continentalsized networks. 1
Hierarchical Hub Labelings for Shortest Paths
 PROCEEDINGS OF THE 20TH ANNUAL EUROPEAN SYMPOSIUM ON ALGORITHMS (ESA’12), VOLUME 7501 OF LECTURE NOTES IN COMPUTER SCIENCE
, 2012
"... We study hierarchical hub labelings for computing shortest paths. Our new theoretical insights into the structure of hierarchical labels lead to faster preprocessing algorithms, making the labeling approach practical for a wider class of graphs. We also find smaller labels for road networks, impro ..."
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Cited by 20 (10 self)
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We study hierarchical hub labelings for computing shortest paths. Our new theoretical insights into the structure of hierarchical labels lead to faster preprocessing algorithms, making the labeling approach practical for a wider class of graphs. We also find smaller labels for road networks, improving the query speed.
PHAST: hardwareaccelerated shortest path trees
 J. PARALLEL DISTRIB. COMPUT
, 2013
"... We present a novel algorithm to solve the nonnegative singlesource shortest path problem on road networks and graphs with low highway dimension. After a quick preprocessing phase, we can compute all distances from a given source in the graph with essentially a linear sweep over all vertices. Becaus ..."
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Cited by 19 (4 self)
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We present a novel algorithm to solve the nonnegative singlesource shortest path problem on road networks and graphs with low highway dimension. After a quick preprocessing phase, we can compute all distances from a given source in the graph with essentially a linear sweep over all vertices. Because this sweep is independent of the source, we are able to reorder vertices in advance to exploit locality. Moreover, our algorithm takes advantage of features of modern CPU architectures, such as SSE and multiple cores. Compared to Dijkstra’s algorithm, our method needs fewer operations, has better locality, and is better able to exploit parallelism at multicore and instruction levels. We gain additional speedup when implementing our algorithm on a GPU, where it is up to three orders of magnitude faster than Dijkstra’s algorithm on a highend CPU. This makes applications based on allpairs shortestpaths practical for continentalsized road networks. Several algorithms, such as computing the graph diameter, arc flags, or exact reaches, can be greatly accelerated by our method.
Faster Customization of Road Networks
 In Proc. SEA, LNCS
, 2013
"... Abstract. A wide variety of algorithms can answer exact shortestpath queries in real time on continental road networks, but they typically require significant preprocessing effort. Recently, the customizable route planning (CRP) approach has reduced the time to process a new cost function to a frac ..."
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Cited by 13 (5 self)
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Abstract. A wide variety of algorithms can answer exact shortestpath queries in real time on continental road networks, but they typically require significant preprocessing effort. Recently, the customizable route planning (CRP) approach has reduced the time to process a new cost function to a fraction of a minute. We reduce customization time even further, by an order of magnitude. This makes it worthwhile even when a single query is to be run, enabling a host of new applications. 1
Route Planning with Flexible Objective Functions
 IN ALENEX
, 2010
"... We present the first fast route planning algorithm that answers shortest paths queries for a customizable linear combination of two different metrics, e. g. travel time and energy cost, on large scale road networks. The precomputation receives as input a directed graph, two edge weight functions t(e ..."
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Cited by 9 (4 self)
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We present the first fast route planning algorithm that answers shortest paths queries for a customizable linear combination of two different metrics, e. g. travel time and energy cost, on large scale road networks. The precomputation receives as input a directed graph, two edge weight functions t(e) and c(e), and a discrete interval [L, U]. The resulting flexible query algorithm finds for a parameter p ∈ [L, U] an exact shortest path for the edge weight t(e)+p·c(e). This allows for different tradeoffs between the two edge weight functions at query time. We apply precomputation based on node contraction, which adds all necessary shortcuts for any parameter choice efficiently. To improve the node ordering, we developed the new concept of gradual parameter interval splitting. Additionally, we improve performance by combining node contraction and a goaldirected technique in our flexible scenario.
UserConstrained MultiModal Route Planning
"... In the multimodal route planning problem we are given multiple transportation networks (e. g., pedestrian, road, public transit) and ask for a best integrated journey between two points. The main challenge is that a seemingly optimal journey may have changes between networks that do not reflect the ..."
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Cited by 8 (1 self)
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In the multimodal route planning problem we are given multiple transportation networks (e. g., pedestrian, road, public transit) and ask for a best integrated journey between two points. The main challenge is that a seemingly optimal journey may have changes between networks that do not reflect the user’s modal preferences. In fact, quickly computing reasonable multimodal routes remains a challenging problem: Previous approaches either suffer from poor query performance or their available choices of modal preferences during query time is limited. In this work we focus on computing exact multimodal journeys that can be restricted by specifying arbitrary modal sequences at query time. For example, a user can say whether he wants to only use public transit, or also prefers to use a taxi or walking at the beginning or end of the journey; or if he has no restrictions at all. By carefully adapting node contraction, a common ingredient to many speedup techniques on road networks, we are able to compute pointtopoint queries on a continental network combined of cars, railroads and flights several orders of magnitude faster than Dijkstra’s algorithm. Thereby, we require little space overhead and obtain fast preprocessing times.
Optimal Route Planning for Electric Vehicles in Large Network
 In Burgard and Roth [5
"... We consider the problem of routing electric vehicles (EV) in the most energyefficient way within a road network taking into account both their limited energy supply as well as their ability to recuperate energy. Employing a classical result by Johnson and an observation about Dijkstra under nonc ..."
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Cited by 8 (0 self)
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We consider the problem of routing electric vehicles (EV) in the most energyefficient way within a road network taking into account both their limited energy supply as well as their ability to recuperate energy. Employing a classical result by Johnson and an observation about Dijkstra under nonconstant edge costs we obtainO(n log n+m) query time after aO(nm) preprocessing phase for any road network graph whose edge costs represent energy consumption or recuperation. If the energy recuperation is height induced in a very natural way, the preprocessing phase can even be omitted. We then adapt a technique for speedingup (unconstrained) shortest path queries to our scenario to achieve a speedup of another factor of around 20. Our results drastically improve upon the recent results in (Artmeier et al. 2010) and allow for route planning of EVs in an instant even on large networks.
Exact Combinatorial BranchandBound for Graph Bisection
"... We present a novel exact algorithm for the minimum graph bisection problem, whose goal is to partition a graph into two equallysized cells while minimizing the number of edges between them. Our algorithm is based on the branchandbound framework and, unlike most previous approaches, it is fully co ..."
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Cited by 7 (3 self)
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We present a novel exact algorithm for the minimum graph bisection problem, whose goal is to partition a graph into two equallysized cells while minimizing the number of edges between them. Our algorithm is based on the branchandbound framework and, unlike most previous approaches, it is fully combinatorial. We present stronger lower bounds, improved branching rules, and a new decomposition technique that contracts entire regions of the graph without losing optimality guarantees. In practice, our algorithm works particularly well on instances with relatively small minimum bisections, solving large realworld graphs (with tens of thousands to millions of vertices) to optimality.
HLDB: Locationbased services in databases
 In Proceedings of the 20th ACM SIGSPATIAL International Symposium on Advances in Geographic Information Systems (GIS’12), 339–348. ACM Press. Best Paper Award
, 2012
"... This paper introduces HLDB, the first practical system that can answer exact spatial queries on continental road networks entirely within a database. HLDB is based on hub labels (HL), the fastest pointtopoint algorithm for road networks, and its queries are implemented (quite naturally) in stan ..."
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Cited by 5 (2 self)
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This paper introduces HLDB, the first practical system that can answer exact spatial queries on continental road networks entirely within a database. HLDB is based on hub labels (HL), the fastest pointtopoint algorithm for road networks, and its queries are implemented (quite naturally) in standard SQL. Within the database, HLDB answers exact distance queries and retrieves full shortestpath descriptions in real time, even on networks with tens of millions of vertices. The basic algorithm can be extended in a natural way (still in SQL) to answer much more sophisticated queries, such as finding the ten closest fastfood restaurants. We also introduce efficient new HLbased algorithms for even harder problems, such as best via point, ride sharing, and point of interest prediction. The HLDB framework makes it easy to implement these algorithms in SQL, enabling interactive applications on continental road networks.
Recent advances in graph partitioning
 Arxiv
"... Abstract. We survey recent trends in practical algorithms for balanced graph partitioning together with applications and future research directions. 1 ..."
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Cited by 5 (2 self)
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Abstract. We survey recent trends in practical algorithms for balanced graph partitioning together with applications and future research directions. 1