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Importance of information exchange in quasi-parallel genetic algorithms

Authors:

Guan Wang,

Degang Wu,

Wenjin Chen,

Kwok Yip SzetoAuthors Info & Claims

GECCO '11: Proceedings of the 13th annual conference companion on Genetic and evolutionary computation

Pages 127 - 128

https://doi.org/10.1145/2001858.2001931

Published: 12 July 2011 Publication History

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Abstract

In this paper, we make a brief study on the effect of exchange rate in quasi-parallel genetic algorithms. The exchange rate is determined by two elements: the communication topology of the parallel populations and the communication capacity on each link. Here we formulate the communication capacity as the number of chromosomes one population exchanges with its neighbors. To study the effect of the two elements of exchange rate separately we did some tests on the minimization of the Weierstrass Function. Our results show that topology with a larger number of exchanged chromosomes generally yields better performance.

References

[1]

Li, S. P., and Szeto, K. Y. Crytoarithmetic problem using parallel Genetic algorithms. Mendl'99, Brno, Czech, 1999.

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[2]

Jiang, R., Szeto, K.Y., Luo, Y.P., and Hu, D.C. Distributed parallel genetic algorithms with path splitting scheme for the large traveling salesman problems. Proceedings of Conference on Intelligent Information Processing, 16th World Computer Congress 2000, Aug.21--25, 2000, Beijing, Ed. Z. Shi, B. Faltings, and M. Musen, Publishing House of Electronic Industry, 478--485, 2000.

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[3]

Szeto, K.Y., Cheung, K.H., and Li, S. P. Effects of dimensionality on parallel genetic algorithms. Proceedings of the 4th International Conference on Information System, Analysis and Synthesis, Orlando, Florida, USA, Vol.2, 322--325, 1998.

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[4]

Zhao, S.Y., and Szeto, K.Y. Combining Exhaustive Search with Evolutionary Computation via Computational Resource Allocation, CEC2007, Sept.25--28 Singapore, 2007. IEEE Proceeding p1878--1881.

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[5]

Law, N. L., and Szeto, K.Y. Adaptive Genetic algorithms with Mutation and Crossover Matrices; Proceeding of the 12th International Joint Conference on Artificial Intelligence (IJCAI-07) January 6 - 12, 2007 (Volume II) Theme: Al and Its Benefits to Society, Published by International Joint Conferences on Artificial Intelligence, IJCAI-07. Hyderabad, India, pp 2330 -- 2333.

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Wong KSzeto K(2019)Multiple Sources Influence Maximization in Complex Networks with Genetic AlgorithmDistributed Computing and Artificial Intelligence, 16th International Conference10.1007/978-3-030-23887-2_26(226-234)Online publication date: 22-Jun-2019
https://doi.org/10.1007/978-3-030-23887-2_26
Cheung LCheung KSzeto K(2018)Maximizing the Effect of Local Disturbance in the Dynamics of Opinion FormationApplications of Evolutionary Computation10.1007/978-3-319-77538-8_13(171-184)Online publication date: 8-Mar-2018
https://doi.org/10.1007/978-3-319-77538-8_13
Yip CSzeto K(2017)Optimization of Joint Sales Potential Using Genetic AlgorithmHybrid Artificial Intelligent Systems10.1007/978-3-319-59650-1_11(125-136)Online publication date: 2-Jun-2017
https://doi.org/10.1007/978-3-319-59650-1_11
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Index Terms

Importance of information exchange in quasi-parallel genetic algorithms
1. Mathematics of computing
  1. Mathematical analysis
    1. Mathematical optimization
2. Theory of computation
  1. Design and analysis of algorithms
    1. Mathematical optimization

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Published In

GECCO '11: Proceedings of the 13th annual conference companion on Genetic and evolutionary computation

July 2011

1548 pages

ISBN:9781450306904

DOI:10.1145/2001858

Editor:
Natalio Krasnogor
University of Nottingham, UK
,
General Chair:
Pier Luca Lanzi
Politecnico di Milano, Italy

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 July 2011

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GECCO '11

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SIGEVO

GECCO '11: Genetic and Evolutionary Computation Conference

July 12 - 16, 2011

Dublin, Ireland

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

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Wong KSzeto K(2019)Multiple Sources Influence Maximization in Complex Networks with Genetic AlgorithmDistributed Computing and Artificial Intelligence, 16th International Conference10.1007/978-3-030-23887-2_26(226-234)Online publication date: 22-Jun-2019
https://doi.org/10.1007/978-3-030-23887-2_26
Cheung LCheung KSzeto K(2018)Maximizing the Effect of Local Disturbance in the Dynamics of Opinion FormationApplications of Evolutionary Computation10.1007/978-3-319-77538-8_13(171-184)Online publication date: 8-Mar-2018
https://doi.org/10.1007/978-3-319-77538-8_13
Yip CSzeto K(2017)Optimization of Joint Sales Potential Using Genetic AlgorithmHybrid Artificial Intelligent Systems10.1007/978-3-319-59650-1_11(125-136)Online publication date: 2-Jun-2017
https://doi.org/10.1007/978-3-319-59650-1_11
Guan WSzeto K(2013)Topological effects on the performance of island model of parallel genetic algorithmProceedings of the 12th international conference on Artificial Neural Networks: advences in computational intelligence - Volume Part II10.1007/978-3-642-38682-4_2(11-19)Online publication date: 12-Jun-2013
https://dl.acm.org/doi/10.1007/978-3-642-38682-4_2
Wang CSzeto K(2012)Sales potential optimization on directed social networksProceedings of the 2012t European conference on Applications of Evolutionary Computation10.1007/978-3-642-29178-4_12(114-123)Online publication date: 11-Apr-2012
https://dl.acm.org/doi/10.1007/978-3-642-29178-4_12

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