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Some measurements on the effects of the curse of dimensionality

Published: 12 July 2014 Publication History

Abstract

The existence of the curse of dimensionality is well known, and its general effects are well acknowledged. However, perhaps due to this colloquial understanding, specific measurements on the curse of dimensionality and its effects are not as extensive. In continuous domains, the volume of the search space grows exponentially with dimensionality. Conversely, the number of function evaluations budgeted to explore this search space usually grows only linearly. New experiments show that particle swarm optimization and differential evolution have super-linear growth in convergence time as dimensionality grows. When restricted by a linear growth in allotted function evaluations, this super-linear growth in convergence time leads to a decrease in the allowed population size.

References

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Kennedy, J. and Eberhart, R. C. 1995. Particle swarm optimization. In Proceedings of the IEEE International Conference on Neural Networks (Perth, Australia, Nov 27-Dec 01, 1995). ICNN'95. IEEE Press, Piscataway, NJ, 1942--1948. DOI= http://dx.doi.org/10.1109/ICNN.1995.488968.
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Storn, R. 1996. On the usage of differential evolution for function optimization. In Proceedings of the 1996 Biennial Conference of the North American Fuzzy Information Processing Society (Berkeley, USA, June 19-22, 1996). NAFIPS'96. IEEE Press, Piscataway, NJ, 519--523. DOI= http://dx.doi.org/10.1109/NAFIPS.1996.534789.
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Bratton, D. and Kennedy, J. 2007. Defining a standard for particle swarm optimization. In Proceedings of the Swarm Intelligence Symposium (Honolulu, USA, April 01-05, 2007). SIS'07. IEEE Press, Piscataway, NJ, 120--127. DOI= http://dx.doi.org/10.1109/SIS.2007.368035.
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Mallipeddi, R. and Suganthan, P. N. 2008. Empirical study on the effect of population size on differential evolution algorithm. In Proceedings of the IEEE Congress on Evolutionary Computation (Hong Kong, June 01-06, 2008). CEC'08. IEEE Press, Piscataway, NJ, 3663--3670. DOI= http://dx.doi.org/10.1109/CEC.2008.4631294.

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  • (2019)Cooperative Asynchronous Parallel Particle Swarm Optimization for Large Dimensional ProblemsInternational Journal of Applied Metaheuristic Computing10.4018/IJAMC.201907010210:3(19-38)Online publication date: Jul-2019

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    cover image ACM Conferences
    GECCO Comp '14: Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation
    July 2014
    1524 pages
    ISBN:9781450328814
    DOI:10.1145/2598394
    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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    Published: 12 July 2014

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    Author Tags

    1. curse of dimensionality
    2. large scale global optimization

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    GECCO '14
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    GECCO '14: Genetic and Evolutionary Computation Conference
    July 12 - 16, 2014
    BC, Vancouver, Canada

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    GECCO Comp '14 Paper Acceptance Rate 180 of 544 submissions, 33%;
    Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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    • (2019)Cooperative Asynchronous Parallel Particle Swarm Optimization for Large Dimensional ProblemsInternational Journal of Applied Metaheuristic Computing10.4018/IJAMC.201907010210:3(19-38)Online publication date: Jul-2019

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