A biogeography-based optimization algorithm with multiple migrations

Weichao Chai; Hongbin Dong; Jun He; Wenqian Shang

doi:10.1109/ICIS.2016.7550912

A biogeography-based optimization algorithm with multiple migrations

Weichao Chai, Hongbin Dong, Jun He, Wenqian Shang

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference Proceeding (Non-Journal item)

2 Citations (Scopus)

173 Downloads (Pure)

Abstract

Biogeography-based optimization (BBO) is a recently-developed algorithm that uses migration to share information among candidate solutions. We use differential evolution algorithm's mutation operator to improve the individual migration operator, and take an adaptive method in setting the value of the scaling factor. The new individual migration is combined with two traditional gene migrations, thus we get a new multiple migrations operator. The biogeography-based optimization with multiple migrations (HLBBO) is proposed based on this new operator. Experiments have been conducted on 25 benchmarks from the 2005 Congress on Evolutionary Computation. Compared with BBO algorithm and linearized BBO, the results show that the proposed algorithm HLBBO can improve the convergence speed and solution accuracy. And the boxplot of the best fitness value show the algorithm' s stability.

Original language	English
Title of host publication	2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings
Editors	Kuniaki Uehara, Masahide Nakamura
Publisher	IEEE Press
ISBN (Electronic)	9781509008063
DOIs	https://doi.org/10.1109/ICIS.2016.7550912
Publication status	Published - 23 Aug 2016
Event	Computer and Information Science - Okayama, Japan Duration: 26 Jun 2016 → 29 Jun 2016 Conference number: 15

Publication series

Name	2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings

Conference

Conference	Computer and Information Science
Abbreviated title	ICIS-2016
Country/Territory	Japan
City	Okayama
Period	26 Jun 2016 → 29 Jun 2016

Keywords

biogeography-based optimization
gene migration
Individual migration
multiple migrations

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A biogeography-based optimization algorithm with multiple migrationsFinal published version, 373 KB

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Chai, W., Dong, H., He, J., & Shang, W. (2016). A biogeography-based optimization algorithm with multiple migrations. In K. Uehara, & M. Nakamura (Eds.), 2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings Article 7550912 (2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings). IEEE Press. https://doi.org/10.1109/ICIS.2016.7550912

Chai, Weichao ; Dong, Hongbin ; He, Jun et al. / A biogeography-based optimization algorithm with multiple migrations. 2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings. editor / Kuniaki Uehara ; Masahide Nakamura. IEEE Press, 2016. (2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings).

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title = "A biogeography-based optimization algorithm with multiple migrations",

abstract = "Biogeography-based optimization (BBO) is a recently-developed algorithm that uses migration to share information among candidate solutions. We use differential evolution algorithm's mutation operator to improve the individual migration operator, and take an adaptive method in setting the value of the scaling factor. The new individual migration is combined with two traditional gene migrations, thus we get a new multiple migrations operator. The biogeography-based optimization with multiple migrations (HLBBO) is proposed based on this new operator. Experiments have been conducted on 25 benchmarks from the 2005 Congress on Evolutionary Computation. Compared with BBO algorithm and linearized BBO, the results show that the proposed algorithm HLBBO can improve the convergence speed and solution accuracy. And the boxplot of the best fitness value show the algorithm' s stability.",

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author = "Weichao Chai and Hongbin Dong and Jun He and Wenqian Shang",

year = "2016",

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day = "23",

doi = "10.1109/ICIS.2016.7550912",

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editor = "Kuniaki Uehara and Masahide Nakamura",

booktitle = "2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings",

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Chai, W, Dong, H, He, J & Shang, W 2016, A biogeography-based optimization algorithm with multiple migrations. in K Uehara & M Nakamura (eds), 2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings., 7550912, 2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings, IEEE Press, Computer and Information Science, Okayama, Japan, 26 Jun 2016. https://doi.org/10.1109/ICIS.2016.7550912

A biogeography-based optimization algorithm with multiple migrations. / Chai, Weichao; Dong, Hongbin; He, Jun et al.
2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings. ed. / Kuniaki Uehara; Masahide Nakamura. IEEE Press, 2016. 7550912 (2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference Proceeding (Non-Journal item)

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T1 - A biogeography-based optimization algorithm with multiple migrations

AU - Chai, Weichao

AU - Dong, Hongbin

AU - He, Jun

AU - Shang, Wenqian

N1 - Conference code: 15

PY - 2016/8/23

Y1 - 2016/8/23

N2 - Biogeography-based optimization (BBO) is a recently-developed algorithm that uses migration to share information among candidate solutions. We use differential evolution algorithm's mutation operator to improve the individual migration operator, and take an adaptive method in setting the value of the scaling factor. The new individual migration is combined with two traditional gene migrations, thus we get a new multiple migrations operator. The biogeography-based optimization with multiple migrations (HLBBO) is proposed based on this new operator. Experiments have been conducted on 25 benchmarks from the 2005 Congress on Evolutionary Computation. Compared with BBO algorithm and linearized BBO, the results show that the proposed algorithm HLBBO can improve the convergence speed and solution accuracy. And the boxplot of the best fitness value show the algorithm' s stability.

AB - Biogeography-based optimization (BBO) is a recently-developed algorithm that uses migration to share information among candidate solutions. We use differential evolution algorithm's mutation operator to improve the individual migration operator, and take an adaptive method in setting the value of the scaling factor. The new individual migration is combined with two traditional gene migrations, thus we get a new multiple migrations operator. The biogeography-based optimization with multiple migrations (HLBBO) is proposed based on this new operator. Experiments have been conducted on 25 benchmarks from the 2005 Congress on Evolutionary Computation. Compared with BBO algorithm and linearized BBO, the results show that the proposed algorithm HLBBO can improve the convergence speed and solution accuracy. And the boxplot of the best fitness value show the algorithm' s stability.

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Chai W, Dong H, He J, Shang W. A biogeography-based optimization algorithm with multiple migrations. In Uehara K, Nakamura M, editors, 2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings. IEEE Press. 2016. 7550912. (2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings). doi: 10.1109/ICIS.2016.7550912

A biogeography-based optimization algorithm with multiple migrations

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