extended-abstract

A scalable computational approach to political redistricting optimization

Authors:

Yan Y. Liu,

Wendy K. Tam Cho,

Shaowen WangAuthors Info & Claims

XSEDE '15: Proceedings of the 2015 XSEDE Conference: Scientific Advancements Enabled by Enhanced Cyberinfrastructure

Article No.: 6, Pages 1 - 2

https://doi.org/10.1145/2792745.2792751

Published: 26 July 2015 Publication History

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Abstract

We present the experience of developing a scalable computational approach to political redistricting optimization by enhancing a parallel genetic algorithm library on XSEDE and Blue Waters.

References

[1]

M. R. Garey and D. S. Johnson, "Computers and Intractability; A Guide to the Theory of NP-Completeness": W. H. Freeman and Co., 1990.

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[2]

W. K.T. Cho and J. G. Gimpel, "Geographic Information Systems and the Spatial Dimensions of American Politics," Annual Review of Political Science, 15: 443--460, 2012.

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[3]

Y. Y. Liu and S. Wang, "A Scalable Parallel Genetic Algorithm for the Generalized Assignment Problem." Parallel Computing, http://dx.doi.org/10.1016/j.parco.2014.04.008.

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Cited By

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Schutzman ZMarkham APowles JWalsh TWashington A(2020)Trade-offs in Fair RedistrictingProceedings of the AAAI/ACM Conference on AI, Ethics, and Society10.1145/3375627.3375802(159-165)Online publication date: 7-Feb-2020
https://dl.acm.org/doi/10.1145/3375627.3375802
Haq EBraud TKwon YHui P(2020)A Survey on Computational PoliticsIEEE Access10.1109/ACCESS.2020.30349838(197379-197406)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3034983
Bar-Natan ANajt LSchutzman Z(2020)The gerrymandering jumble: map projections permute districts’ compactness scoresCartography and Geographic Information Science10.1080/15230406.2020.173757547:4(321-335)Online publication date: 13-May-2020
https://doi.org/10.1080/15230406.2020.1737575
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Index Terms

A scalable computational approach to political redistricting optimization
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
2. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Distributed systems organizing principles

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Published In

XSEDE '15: Proceedings of the 2015 XSEDE Conference: Scientific Advancements Enabled by Enhanced Cyberinfrastructure

July 2015

296 pages

ISBN:9781450337205

DOI:10.1145/2792745

General Chair:
Gregory D. Peterson
National Institute of Computational Sciences

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 July 2015

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Extended-abstract

Funding Sources

National Science Foundation

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XSEDE '15

Sponsor:

San Diego Super Computing Ctr
HPCWire
Omnibond
Indiana University
CASC
NICS
Intel
DDN
CORSA
ALLINEA
RENCI

XSEDE '15: Extreme Science Engineering Discovery Environment 2015 Conference

July 26 - 30, 2015

Missouri, St. Louis

Acceptance Rates

XSEDE '15 Paper Acceptance Rate 49 of 70 submissions, 70%;

Overall Acceptance Rate 129 of 190 submissions, 68%

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Schutzman ZMarkham APowles JWalsh TWashington A(2020)Trade-offs in Fair RedistrictingProceedings of the AAAI/ACM Conference on AI, Ethics, and Society10.1145/3375627.3375802(159-165)Online publication date: 7-Feb-2020
https://dl.acm.org/doi/10.1145/3375627.3375802
Haq EBraud TKwon YHui P(2020)A Survey on Computational PoliticsIEEE Access10.1109/ACCESS.2020.30349838(197379-197406)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3034983
Bar-Natan ANajt LSchutzman Z(2020)The gerrymandering jumble: map projections permute districts’ compactness scoresCartography and Geographic Information Science10.1080/15230406.2020.173757547:4(321-335)Online publication date: 13-May-2020
https://doi.org/10.1080/15230406.2020.1737575
Liu YCho WWang S(2016)PEAR: a massively parallel evolutionary computation approach for political redistricting optimization and analysisSwarm and Evolutionary Computation10.1016/j.swevo.2016.04.00430(78-92)Online publication date: Oct-2016
https://doi.org/10.1016/j.swevo.2016.04.004

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Political redistricting by computer

An improved genetic algorithm with conditional genetic operators and its application to set-covering problem

MPPs and clusters for scalable computing

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