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A Parallel Algorithm to Solve Near-Shortest Path Problems on Raster Graphs

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Modern Accelerator Technologies for Geographic Information Science

Abstract

The Near-Shortest Path (NSP) algorithm (Carlyle and Wood, Networks 46(2): 98–109, 2005; Medrano and Church, GeoTrans RP-01-12-01, UC Santa Barbara, 2012) has been identified as being effective at generating sets of good route alternatives for designing new infrastructure. While the algorithm itself is faster than other enumerative shortest path set approaches including the Kth-shortest path problem, the solution set size and computation time grow exponentially as the problem size or parameters increase, and requires the use of high-performance parallel computing to solve for real-world problems. We present a new breadth-first-search parallelization of the NSP algorithm. Computational results and future work for parallel efficiency improvements are discussed.

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Acknowledgements

We would like to thank the Environmental Sciences Division of Argonne National Laboratories for providing the funding to conduct this research (1F-32422).

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Authors and Affiliations

  1. Department of Geography, University of California at Santa Barbara, Santa Barbara, CA, USA

    F. Antonio Medrano & Richard L. Church

Authors
  1. F. Antonio Medrano
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  2. Richard L. Church
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Correspondence to F. Antonio Medrano .

Editor information

Editors and Affiliations

  1. Department of Geosciences, University of Arkansas, Fayetteville, Arkansas, USA

    Xuan Shi

  2. Department of Electrical and Computer Engineering, University of Illinois, Urbana, Illinois, USA

    Volodymyr Kindratenko

  3. Department of Geography and GeoInformation Sciences, George Mason University, Fairfax, Virginia, USA

    Chaowei Yang

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Medrano, F.A., Church, R.L. (2013). A Parallel Algorithm to Solve Near-Shortest Path Problems on Raster Graphs. In: Shi, X., Kindratenko, V., Yang, C. (eds) Modern Accelerator Technologies for Geographic Information Science. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-8745-6_7

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  • DOI: https://doi.org/10.1007/978-1-4614-8745-6_7

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  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4614-8744-9

  • Online ISBN: 978-1-4614-8745-6

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