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Black-box optimization benchmarking of prototype optimization with evolved improvement steps for noiseless function testbed

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GECCO '09: Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers

Pages 2303 - 2308

https://doi.org/10.1145/1570256.1570321

Published: 08 July 2009 Publication History

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Abstract

This paper presents benchmarking of a stochastic local search algorithm called Prototype Optimization with Evolved Improvement Steps (POEMS) on the noise-free BBOB 2009 testbed. Experiments for 2, 3, 5, 10 and 20 D were done, where D denotes the search space dimension. The maximum number of function evaluations is chosen as 10⁵ x D. Experimental results show that POEMS performs best on all separable functions and the attractive sector function. It works also quite well on multi-modal functions with lower dimensions. On the other hand, the algorithm fails to solve functions with high conditioning.

References

[1]

J. Kubalik and J. Faigl. Iterative Prototype Optimisation with Evolved Improvement Steps. In: P. Collet, M. Tomassini, M. Ebner, A. Ekart and S. Gustafson (Eds.): Proceedings of the 9th European Conference on Genetic Programming, EuroGP 2006, Heidelberg: Springer, pp. 154--165, 2006.

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[2]

J. Kubalik. Real-Parameter Optimization by Iterative Prototype Optimization with Evolved Improvement Steps. In: 2006IEEE Congress on Evolutionary Computation {CD-ROM}. Los Alamitos: IEEE Computer Society, pp. 6823--6829, 2006.

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J. Kubalik Solving the Sorting Network Problem Using Iterative Optimization with Evolved Hypermutations. Accepted for presentation at GECCO 2009, July 8--12, Montréal Québec, Canada, 2009.

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J. Kubalik. Solving Multiple Sequence Alignment Problem Using Prototype Optimization with Evolved Improvement Steps. Accepted for presentation at the ICANNGA 2009, Kuopio, Finland, 23--25, April, 2009.

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S. Finck, N. Hansen, R. Ros, and A. Auger. Real-parameter black--box optimization benchmarking 2009: Presentation of the noiseless functions. Technical Report 2009/20, Research Center PPE, 2009.

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N. Hansen, A. Auger, S. Finck, and R. Ros. Real-parameter black--box optimization benchmarking 2009: Experimental setup. Technical Report RR-6828, INRIA, 2009.

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N. Hansen, S. Finck, R. Ros, and A. Auger. Real-parameter black-box optimization benchmarking 2009: Noiseless functions definitions. Technical Report RR-6829, INRIA, 2009.

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Cited By

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Llanza AShvai NNakib A(2023)Investigating Fractal Decomposition Based Algorithm on Low-Dimensional Continuous Optimization ProblemsMetaheuristics10.1007/978-3-031-26504-4_16(215-229)Online publication date: 23-Feb-2023
https://doi.org/10.1007/978-3-031-26504-4_16
Pošík PKubalík J(2012)Experimental Comparison of Six Population-Based Algorithms for Continuous Black Box OptimizationEvolutionary Computation10.1162/EVCO_a_0008320:4(483-508)Online publication date: Dec-2012
https://doi.org/10.1162/EVCO_a_00083
Pošík PKubalik JPelikan MBranke J(2010)Comparison of cauchy EDA and pPOEMS algorithms on the BBOB noiseless testbedProceedings of the 12th annual conference companion on Genetic and evolutionary computation10.1145/1830761.1830792(1703-1710)Online publication date: 7-Jul-2010
https://dl.acm.org/doi/10.1145/1830761.1830792
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Index Terms

Black-box optimization benchmarking of prototype optimization with evolved improvement steps for noiseless function testbed
1. Mathematics of computing
  1. Mathematical analysis
    1. Mathematical optimization
    2. Numerical analysis
2. Theory of computation
  1. Design and analysis of algorithms
    1. Mathematical optimization

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Published In

GECCO '09: Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers

July 2009

1760 pages

ISBN:9781605585055

DOI:10.1145/1570256

General Chair:
Franz Rothlauf
University of Mainz, Germany

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 08 July 2009

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Technical-note

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GECCO09

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GECCO09: Genetic and Evolutionary Computation Conference

July 8 - 12, 2009

Québec, Montreal, Canada

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

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Llanza AShvai NNakib A(2023)Investigating Fractal Decomposition Based Algorithm on Low-Dimensional Continuous Optimization ProblemsMetaheuristics10.1007/978-3-031-26504-4_16(215-229)Online publication date: 23-Feb-2023
https://doi.org/10.1007/978-3-031-26504-4_16
Pošík PKubalík J(2012)Experimental Comparison of Six Population-Based Algorithms for Continuous Black Box OptimizationEvolutionary Computation10.1162/EVCO_a_0008320:4(483-508)Online publication date: Dec-2012
https://doi.org/10.1162/EVCO_a_00083
Pošík PKubalik JPelikan MBranke J(2010)Comparison of cauchy EDA and pPOEMS algorithms on the BBOB noiseless testbedProceedings of the 12th annual conference companion on Genetic and evolutionary computation10.1145/1830761.1830792(1703-1710)Online publication date: 7-Jul-2010
https://dl.acm.org/doi/10.1145/1830761.1830792
Hansen NAuger ARos RFinck SPošík PPelikan MBranke J(2010)Comparing results of 31 algorithms from the black-box optimization benchmarking BBOB-2009Proceedings of the 12th annual conference companion on Genetic and evolutionary computation10.1145/1830761.1830790(1689-1696)Online publication date: 7-Jul-2010
https://dl.acm.org/doi/10.1145/1830761.1830790
Kubalik JPelikan MBranke J(2010)Black-box optimization benchmarking of two variants of the POEMS algorithm on the noiseless testbedProceedings of the 12th annual conference companion on Genetic and evolutionary computation10.1145/1830761.1830774(1567-1574)Online publication date: 7-Jul-2010
https://dl.acm.org/doi/10.1145/1830761.1830774

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