research-article

Parallel Island-Based Genetic Algorithm for Radio Network Design

Authors:

Patrice Calégari,

Frédéric Guidec,

Pierre Kuonen,

Daniel KoblerAuthors Info & Claims

Journal of Parallel and Distributed Computing, Volume 47, Issue 1

Pages 86 - 90

https://doi.org/10.1006/jpdc.1997.1397

Published: 25 November 1997 Publication History

Abstract

This paper uses a realistic combinatorial optimization problem as an example to show how a genetic algorithm can be parallelized in an efficient way. The problem considered is the selection of the best set of transmitter locations in order to cover a given geographical region at optimal cost. It is shown that it is possible to obtain good solutions to the problem even with a very low communication load. The parallel program is tested, first on an artificial example, then on a real-life case.

References

[1]

P. Calégari, P. Kuonen, F. Guidec, D. Wagner, May 1997, A genetic approach to radio network optimization for mobile systems, Proceedings of the IEEE 47th Vehicular Technology Conference (VTC), 2, 755, 759

Google Scholar

[2]

E. Cantù-Paz, A summary of research on parallel genetic algorithms, Technical Report (1995).

Google Scholar

[3]

A. Colorni, M. Dorigo, V. Maniezzo, Distributed optimization by ant colonies, Bradford Books, 1991.

Google Scholar

[4]

L. Davis, Van Nostrand¿Reinhold, New York, 1991.

Google Scholar

[5]

M. Garey, D. Johnson, Freeman, New York, 1979.

Google Scholar

[6]

F. Glover, Genetic algorithms and scatter search: Unsuspected potentials, Statist. Comput., 4 (1994) 131-140.

Crossref

Google Scholar

[7]

D. Goldberg, Addison-Wesley, Reading, 1989.

Google Scholar

[8]

P. Kuonen, S. Josselin, S. Ubéda, D. Wagner, Apr. 1996, Parallel computing of radio coverage, Proceedings of the IEEE VTC 46th Vehicular Technology Conference (VTC), 3, 1438, 1442

Google Scholar

[9]

R. Tanese, 1989, Distributed genetic algorithms, Second International Conference on Genetic Algorithms, J. SchafferP. Laboratories, Morgan Kaufmann, San Mateo, CA

Google Scholar

[10]

D. Whitley, A genetic algorithm tutorial, Technical Report, CS-93-103 (1993).

Google Scholar

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Nassiri MEtemadi Borujeni S(2021)A novel approach on femtocell placement in the commercial buildings using genetic algorithmTransactions on Emerging Telecommunications Technologies10.1002/ett.428532:9Online publication date: 8-Sep-2021
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Index Terms

Parallel Island-Based Genetic Algorithm for Radio Network Design
1. Theory of computation
  1. Design and analysis of algorithms

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Published In

cover image Journal of Parallel and Distributed Computing

Journal of Parallel and Distributed Computing Volume 47, Issue 1

Special issue on parallel evolutionary computing

Nov. 25, 1997

97 pages

ISSN:0743-7315

Editors:
Allan Gottlieb
NEC Research Institute, Princeton, NJ
,
Kai Hwang
Univ. of Hong Kong, Hong Kong
,
Sartaj Sahni
Univ. of Florida, Gainesville
,
Albert Y. Zomaya
Univ. of Western Australia, Perth, W.A., Australia
,
Stephan Olariu
Old Dominion Univ., Norfolk, VA

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Academic Press, Inc.

United States

Publication History

Published: 25 November 1997

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Nassiri MEtemadi Borujeni S(2021)A novel approach on femtocell placement in the commercial buildings using genetic algorithmTransactions on Emerging Telecommunications Technologies10.1002/ett.428532:9Online publication date: 8-Sep-2021
https://dl.acm.org/doi/10.1002/ett.4285
Dahi ZMezioud CDraa A(2016)On the efficiency of the binary flower pollination algorithmApplied Soft Computing10.1016/j.asoc.2016.05.05147:C(395-414)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1016/j.asoc.2016.05.051
Song JGuan SZheng B(2014)Incremental Hyper-Sphere Partitioning for ClassificationInternational Journal of Applied Evolutionary Computation10.4018/ijaec.20140401055:2(72-88)Online publication date: 1-Apr-2014
https://dl.acm.org/doi/10.4018/ijaec.2014040105
Osaba EDiaz FOnieva E(2014)Golden ballApplied Intelligence10.1007/s10489-013-0512-y41:1(145-166)Online publication date: 1-Jul-2014
https://dl.acm.org/doi/10.1007/s10489-013-0512-y
Yang TGuan SSong JZheng BCao MYu T(2013)Incremental Hyperplane Partitioning for ClassificationInternational Journal of Applied Evolutionary Computation10.4018/jaec.20130401064:2(67-79)Online publication date: 1-Apr-2013
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To CElati MAlba E(2013)A parallel genetic programming for single class classificationProceedings of the 15th annual conference companion on Genetic and evolutionary computation10.1145/2464576.2466811(1579-1586)Online publication date: 6-Jul-2013
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Gomez-Pulido JVega-Rodriguez MSanchez-Perez JPriem-Mendes SCarreira V(2011)Accelerating floating-point fitness functions in evolutionary algorithmsGenetic Programming and Evolvable Machines10.1007/s10710-011-9137-212:4(403-427)Online publication date: 1-Dec-2011
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Luque GLuna FAlba ENesmachnow S(2011)Exploring the accuracy of a parallel cooperative model for trajectory-based metaheuristicsProceedings of the 13th international conference on Computer Aided Systems Theory - Volume Part I10.1007/978-3-642-27549-4_41(319-326)Online publication date: 6-Feb-2011
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Segura CGonzález YMiranda GLeón C(2010)A multi-objective evolutionary approach for the antenna positioning problemProceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I10.5555/1893893.1893904(51-60)Online publication date: 8-Sep-2010
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To CPham T(2009)Understanding predictability of bio-signals using genetic algorithms and sample entropyProceedings of the 2nd WSEAS international conference on Biomedical electronics and biomedical informatics10.5555/1946539.1946548(47-51)Online publication date: 20-Aug-2009
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