Years and Authors of Summarized Original Work
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2002; Schulz, Wagner, Zaroliagis
Problem Definition
Dealing effectively with applications in large networks, it typically requires the efficient solution of one ore more underlying algorithmic problems. Due to the size of the network, a considerable effort is inevitable in order to achieve the desired efficiency in the algorithm.
One of the primary tasks in large network applications is to answer queries for finding best routes or paths as efficiently as possible. Quite often, the challenge is to process a vast number of such queries on-line: a typical situation encountered in several real-time applications (e.g., traffic information systems, public transportation systems) concerns a query‐intensive scenario, where a central server has to answer a huge number of on-line customer queries asking for their best routes (or optimal itineraries). The main goal in such an application is to reduce the (average) response time for a query.
Answering...
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Delling D, Holzer M, Müller K, Schulz F, Wagner D (2006) High-performance multi-level graphs. In: 9th DIMACS challenge on shortest paths, Rutgers University, Nov 2006
Delling D, Sanders P, Schultes D, Wagner D (2006) Highway hierarchies star. In: 9th DIMACS challenge on shortest paths, Rutgers University, Nov 2006
Goldberg AV, Harrelson C (2005) Computing the shortest path: A* search meets graph theory. In: Proceedings of the 16th ACM-SIAM symposium on discrete algorithms – SODA. ACM, New York/SIAM, Philadelphia, pp 156–165
Gutman R (2004) Reach-based routing: a new approach to shortest path algorithms optimized for road networks. In: Algorithm engineering and experiments – ALENEX (SIAM, 2004). SIAM, Philadelphia, pp 100–111
Holzer M, Schulz F, Wagner D (2006) Engineering multi-level overlay graphs for shortest-path queries. In: Algorithm engineering and experiments – ALENEX (SIAM, 2006). SIAM, Philadelphia, pp 156–170
Pyrga E, Schulz F, Wagner D, Zaroliagis C (2007) Efficient models for timetable information in public transportation systems. ACM J Exp Algorithmic 12(2.4):1–39
Sanders P, Schultes D (2005) Highway hierarchies hasten exact shortest path queries. In: Algorithms – ESA 2005. Lecture notes in computer science, vol 3669. pp 568–579
Sanders P, Schultes D (2006) Engineering highway hierarchies. In: Algorithms – ESA 2006. Lecture notes in computer science, vol 4168. pp 804–816
Schulz F, Wagner D, Weihe K (2000) Dijkstra’s algorithm on-line: an empirical case study from public railroad transport. ACM J Exp Algorithmics 5(12):1–23
Schulz F, Wagner D, Zaroliagis C (2002) Using multi-level graphs for timetable information in railway systems. In: Algorithm engineering and experiments – ALENEX 2002. Lecture notes in computer science, vol 2409. pp 43–59
Wagner D, Willhalm T, Zaroliagis C (2005) Geometric containers for efficient shortest path computation. ACM J Exp Algorithm 10(1.3):1–30
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Zaroliagis, C. (2016). Engineering Algorithms for Large Network Applications. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2864-4_125
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