Article

Self-Adaptive Genetic Algorithm for Numeric Functions

Authors:

Robert Hinterding,

Zbigniew Michalewicz,

Thomas C. PeacheyAuthors Info & Claims

PPSN IV: Proceedings of the 4th International Conference on Parallel Problem Solving from Nature

Pages 420 - 429

Published: 22 September 1996 Publication History

Abstract

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Abdou WBloch CCharlet DSpies FMoore J(2012)Adaptive multi-objective genetic algorithm using multi-pareto-rankingProceedings of the 14th annual conference on Genetic and evolutionary computation10.1145/2330163.2330228(449-456)Online publication date: 7-Jul-2012
https://dl.acm.org/doi/10.1145/2330163.2330228
Fernandez-Prieto JCanada-Bago JGadeo-Martos MVelasco J(2012)Optimisation of control parameters for genetic algorithms to test computer networks under realistic traffic loadsApplied Soft Computing10.1016/j.asoc.2012.04.01812:7(1875-1883)Online publication date: 1-Jul-2012
https://dl.acm.org/doi/10.1016/j.asoc.2012.04.018
Fernandez-Prieto JCanada-Bago JGadeo-Martos MVelasco J(2011)Optimisation of control parameters for genetic algorithms to test computer networks under realistic traffic loadsApplied Soft Computing10.1016/j.asoc.2011.02.00411:4(3744-3752)Online publication date: 1-Jun-2011
https://dl.acm.org/doi/10.1016/j.asoc.2011.02.004
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Self-Adaptive Genetic Algorithm for Numeric Functions
1. Applied computing
  1. Life and medical sciences
2. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies

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PPSN IV: Proceedings of the 4th International Conference on Parallel Problem Solving from Nature

September 1996

1021 pages

ISBN:354061723X

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 22 September 1996

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Abdou WBloch CCharlet DSpies FMoore J(2012)Adaptive multi-objective genetic algorithm using multi-pareto-rankingProceedings of the 14th annual conference on Genetic and evolutionary computation10.1145/2330163.2330228(449-456)Online publication date: 7-Jul-2012
https://dl.acm.org/doi/10.1145/2330163.2330228
Fernandez-Prieto JCanada-Bago JGadeo-Martos MVelasco J(2012)Optimisation of control parameters for genetic algorithms to test computer networks under realistic traffic loadsApplied Soft Computing10.1016/j.asoc.2012.04.01812:7(1875-1883)Online publication date: 1-Jul-2012
https://dl.acm.org/doi/10.1016/j.asoc.2012.04.018
Fernandez-Prieto JCanada-Bago JGadeo-Martos MVelasco J(2011)Optimisation of control parameters for genetic algorithms to test computer networks under realistic traffic loadsApplied Soft Computing10.1016/j.asoc.2011.02.00411:4(3744-3752)Online publication date: 1-Jun-2011
https://dl.acm.org/doi/10.1016/j.asoc.2011.02.004
García-Villoria APastor R(2009)Introducing dynamic diversity into a discrete particle swarm optimizationComputers and Operations Research10.1016/j.cor.2007.12.00136:3(951-966)Online publication date: 1-Mar-2009
https://dl.acm.org/doi/10.1016/j.cor.2007.12.001
Srinivasa KVenugopal KPatnaik L(2007)A self-adaptive migration model genetic algorithm for data mining applicationsInformation Sciences: an International Journal10.1016/j.ins.2007.05.008177:20(4295-4313)Online publication date: 1-Oct-2007
https://dl.acm.org/doi/10.1016/j.ins.2007.05.008
Giger MKeller DErmanni P(2007)AORCEA - An adaptive operator rate controlled evolutionary algorithmComputers and Structures10.1016/j.compstruc.2006.12.00285:19-20(1547-1561)Online publication date: 1-Oct-2007
https://dl.acm.org/doi/10.1016/j.compstruc.2006.12.002
Yamina MLaskri M(2005)An evolutionary machine learning: An adaptability perspective at fine granularityInternational Journal of Knowledge-based and Intelligent Engineering Systems10.5555/1233828.12338309:1(13-20)Online publication date: 1-Jan-2005
https://dl.acm.org/doi/10.5555/1233828.1233830
Lobo FLima CRothlauf F(2005)A review of adaptive population sizing schemes in genetic algorithmsProceedings of the 7th annual workshop on Genetic and evolutionary computation10.1145/1102256.1102310(228-234)Online publication date: 25-Jun-2005
https://dl.acm.org/doi/10.1145/1102256.1102310
Srinivasa KSridharan KShenoy PVenugopal KPatnaik L(2005)A dynamic migration model for self-adaptive genetic algorithmsProceedings of the 6th international conference on Intelligent Data Engineering and Automated Learning10.1007/11508069_72(555-562)Online publication date: 6-Jul-2005
https://dl.acm.org/doi/10.1007/11508069_72
Alba ELuna FNebro ATroya J(2004)Parallel heterogeneous genetic algorithms for continuous optimizationParallel Computing10.1016/j.parco.2003.12.01130:5-6(699-719)Online publication date: 1-May-2004
https://dl.acm.org/doi/10.1016/j.parco.2003.12.011
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Kursawe and ZDT functions optimization using hybrid micro genetic algorithm (HMGA)

An improved genetic algorithm encoded by adaptive degressive ary number

Convergence of nomadic genetic algorithm on benchmark mathematical functions

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