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Migration of probabilistic models for island-based bivariate EDA algorithm

Published: 07 July 2007 Publication History

Abstract

The paper presents a new concept of parallel bivariate EDA algorithm using the island-based model with the ring topology. The traditional migration of individuals is compared with a newly proposed technique for the migration of probabilistic models.

References

[1]
Pelikan, M., Möhlenbein, H. The bivariate marginal distribution algorithm. In Advances in Soft Computing - Engineering Design and Manufacturing, Springer-Verlag, pp. 521--535, London, 1999.
[2]
Baluja, S. Population-Based Incremental Learning: A method for Integrating Genetic Search Based Function Optimization and Competitive Learning. Technical report CMU-CS-94-163, Carnegie Mellon University, 1994.

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  • (2010)A Review on Parallel Estimation of Distribution AlgorithmsParallel and Distributed Computational Intelligence10.1007/978-3-642-10675-0_7(143-163)Online publication date: 2010

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  1. Migration of probabilistic models for island-based bivariate EDA algorithm

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      cover image ACM Conferences
      GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
      July 2007
      2313 pages
      ISBN:9781595936974
      DOI:10.1145/1276958

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      Association for Computing Machinery

      New York, NY, United States

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      Published: 07 July 2007

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      Author Tags

      1. EDA algorithms
      2. evolutionary algorithms
      3. island-based models
      4. learning of probabilistic models
      5. migration

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      GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
      Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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      • (2010)A Review on Parallel Estimation of Distribution AlgorithmsParallel and Distributed Computational Intelligence10.1007/978-3-642-10675-0_7(143-163)Online publication date: 2010

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