Results 1  10
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27
Reach for A∗: Efficient pointtopoint shortest path algorithms
 IN WORKSHOP ON ALGORITHM ENGINEERING & EXPERIMENTS
, 2006
"... We study the pointtopoint shortest path problem in a setting where preprocessing is allowed. We improve the reachbased approach of Gutman [16] in several ways. In particular, we introduce a bidirectional version of the algorithm that uses implicit lower bounds and we add shortcut arcs which reduc ..."
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Cited by 58 (5 self)
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We study the pointtopoint shortest path problem in a setting where preprocessing is allowed. We improve the reachbased approach of Gutman [16] in several ways. In particular, we introduce a bidirectional version of the algorithm that uses implicit lower bounds and we add shortcut arcs which reduce vertex reaches. Our modifications greatly reduce both preprocessing and query times. The resulting algorithm is as fast as the best previous method, due to Sanders and Schultes [27]. However, our algorithm is simpler and combines in a natural way with A∗ search, which yields significantly better query times.
NegativeCycle Detection Algorithms
 MATHEMATICAL PROGRAMMING
, 1996
"... We study the problem of finding a negative length cycle in a network. An algorithm for the negative cycle problem combines a shortest path algorithm and a cycle detection strategy. We study various combinations of shortest path algorithms and cycle detection strategies and find the best combinations ..."
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Cited by 46 (5 self)
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We study the problem of finding a negative length cycle in a network. An algorithm for the negative cycle problem combines a shortest path algorithm and a cycle detection strategy. We study various combinations of shortest path algorithms and cycle detection strategies and find the best combinations. One of our discoveries is that a cycle detection strategy of Tarjan greatly improves practical performance of a classical shortest path algorithm, making it competitive with the fastest known algorithms on a wide range of problems. As a part of our study, we develop problem families for testing negative cycle algorithms.
A Simple Shortest Path Algorithm with Linear Average Time
"... We present a simple shortest path algorithm. If the input lengths are positive and uniformly distributed, the algorithm runs in linear time. The worstcase running time of the algorithm is O(m + n log C), where n and m are the number of vertices and arcs of the input graph, respectively, and C i ..."
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Cited by 34 (6 self)
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We present a simple shortest path algorithm. If the input lengths are positive and uniformly distributed, the algorithm runs in linear time. The worstcase running time of the algorithm is O(m + n log C), where n and m are the number of vertices and arcs of the input graph, respectively, and C is the ratio of the largest and the smallest nonzero arc length.
Incorporating Efficient Operations Research Algorithms in ConstraintBased Scheduling
 IN PROCEEDINGS OF THE FIRST INTERNATIONAL JOINT WORKSHOP ON ARTIFICIAL INTELLIGENCE AND OPERATIONS RESEARCH
, 1995
"... We address the area of scheduling and the differences between the way operations research and artificial intelligence approach scheduling. We introduce the concept of constraint programming, and describe how operations research techniques can be integrated in constraint programming. Finally, we ..."
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Cited by 30 (0 self)
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We address the area of scheduling and the differences between the way operations research and artificial intelligence approach scheduling. We introduce the concept of constraint programming, and describe how operations research techniques can be integrated in constraint programming. Finally, we give a short overview of the results obtained with our approach.
Shortest Path Algorithms: Engineering Aspects
 In Proc. ESAAC ’01, Lecture Notes in Computer Science
, 2001
"... We review shortest path algorithms based on the multilevel bucket data structure [6] and discuss the interplay between theory and engineering choices that leads to e#cient implementations. Our experimental results suggest that the caliber heuristic [17] and adaptive parameter selection give an ..."
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Cited by 20 (3 self)
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We review shortest path algorithms based on the multilevel bucket data structure [6] and discuss the interplay between theory and engineering choices that leads to e#cient implementations. Our experimental results suggest that the caliber heuristic [17] and adaptive parameter selection give an e#cient algorithm, both on typical and on hard inputs, for a wide range of arc lengths.
Combinatorial Approximation Algorithms for Generalized Flow Problems
 In ACM/SIAM
, 1999
"... Generalized network flow problems generalize normal network flow problems by specifying a flow multiplier (a) for each arc a. For every unit of flow entering the arc, (a) units of flow exit. Flow multipliers permit modelling transforming one type into another and modification of the amount of flow ..."
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Cited by 10 (1 self)
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Generalized network flow problems generalize normal network flow problems by specifying a flow multiplier (a) for each arc a. For every unit of flow entering the arc, (a) units of flow exit. Flow multipliers permit modelling transforming one type into another and modification of the amount of flow.
The Inverse Shortest Paths Problem With Upper Bounds on Shortest Paths Costs
, 1997
"... We examine the computational complexity of the inverse shortest paths problem with upper bounds on shortest path costs, and prove that obtaining a globally optimum solution to this problem is NPcomplete. An algorithm for finding a locally optimum solution is proposed, discussed and tested. ..."
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Cited by 9 (1 self)
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We examine the computational complexity of the inverse shortest paths problem with upper bounds on shortest path costs, and prove that obtaining a globally optimum solution to this problem is NPcomplete. An algorithm for finding a locally optimum solution is proposed, discussed and tested.
PointtoPoint Shortest Path Algorithms with Preprocessing
"... Abstract. This is a survey of some recent results on pointtopoint shortest path algorithms. This classical optimization problem received a lot of attention lately and significant progress has been made. After an overview of classical results, we study recent heuristics that solve the problem while ..."
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Cited by 4 (0 self)
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Abstract. This is a survey of some recent results on pointtopoint shortest path algorithms. This classical optimization problem received a lot of attention lately and significant progress has been made. After an overview of classical results, we study recent heuristics that solve the problem while examining only a small portion of the input graph; the graph can be very big. Note that the algorithms we discuss find exact shortest paths. These algorithms are heuristic because they perform well only on some graph classes. While their performance has been good in experimental studies, no theoretical bounds are known to support the experimental observations. Most of these algorithms have been motivated by finding paths in large road networks. We start by reviewing the classical Dijkstra’s algorithm and its bidirectional variant, developed in 1950’s and 1960’s. Then we review A* search, an AI technique developed in 1970’s. Next we turn our attention to modern results which are based on preprocessing the graph. To be practical, preprocessing needs to be reasonably fast and not use too much space. We discuss landmark and reachbased algorithms as well as their combination. 1
Nondecreasing paths in weighted graphs, or: how to optimally read a train schedule
 In Proc. SODA
, 2008
"... A travel booking office has timetables giving arrival and departure times for all scheduled trains, including their origins and destinations. A customer presents a starting city and demands a route with perhaps several train connections taking him to his destination as early as possible. The booking ..."
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Cited by 4 (2 self)
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A travel booking office has timetables giving arrival and departure times for all scheduled trains, including their origins and destinations. A customer presents a starting city and demands a route with perhaps several train connections taking him to his destination as early as possible. The booking office must find the best route for its customers. This problem was first considered in the theory of algorithms by George Minty [Min58], who reduced it to a problem on directed weighted graphs: find a path from a given source to a given target such that the consecutive weights on the path are nondecreasing and the last weight on the path is minimized. Minty gave the first algorithm for the single source version of the problem, in which one finds minimum last weight nondecreasing paths from the source to every other vertex. In this paper we give the first linear time algorithm for this problem. We also define an all pairs version for the problem and give a strongly polynomial truly subcubic algorithm for it. 1