An Improved Bat Algorithm Based on Hybrid with Ant Lion Optimizer

Thi-Kien Dao; Shu-Chuan Chu; Jeng-Shyang Pan; Trong-The Nguyen; Truong-Giang Ngo; Trinh-Dong Nguyen; Huu-Trung Tran

doi:10.1007/978-981-15-3308-2_6

An Improved Bat Algorithm Based on Hybrid with Ant Lion Optimizer

Thi-Kien Dao, Shu-Chuan Chu, Jeng-Shyang Pan, Trong-The Nguyen, Truong-Giang Ngo, Trinh-Dong Nguyen, Huu-Trung Tran

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

7 Citations (Scopus)

Abstract

Bat Algorithm (BA) is one of the fundamental algorithms for solving optimization problems. However, the BA still exists weaknesses in terms of exploitation and exploration. In this paper, an enhancing capability of exploration and exploitation for BA by hybridizing BA with Ant Lion Optimizer (ALO) is proposed for the global optimization problems. In the experimental section, several benchmark functions are used to test the performance of the proposed approach. Compared results with other algorithms literature show that the proposed method provides a new competitive algorithm.

Original language	English
Title of host publication	Genetic and Evolutionary Computing
Subtitle of host publication	Proceedings of the 13th International Conference on Genetic and Evolutionary Computing, 2019
Editors	Jeng-Shyang Pan, Jerry Chun-Wei Lin, Yongquan Liang, Shu-Chuan Chu
Place of Publication	Singapore
Publisher	Springer
Pages	50-60
Number of pages	11
ISBN (Electronic)	9789811533082
ISBN (Print)	9789811533075
DOIs	https://doi.org/10.1007/978-981-15-3308-2_6
Publication status	Published - 1 Jan 2020
Externally published	Yes

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1107 AISC
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Keywords

Ant Lion Optimizer
Bat algorithm
Improved Bat algorithm
Optimization

Access to Document

10.1007/978-981-15-3308-2_6Licence: In Copyright

https://rdcu.be/dA71rLicence: In Copyright

Cite this

Dao, T.-K., Chu, S.-C., Pan, J.-S., Nguyen, T.-T., Ngo, T.-G., Nguyen, T.-D., & Tran, H.-T. (2020). An Improved Bat Algorithm Based on Hybrid with Ant Lion Optimizer. In J.-S. Pan, J. C.-W. Lin, Y. Liang, & S.-C. Chu (Eds.), Genetic and Evolutionary Computing: Proceedings of the 13th International Conference on Genetic and Evolutionary Computing, 2019 (pp. 50-60). (Advances in Intelligent Systems and Computing; Vol. 1107 AISC). Springer . https://doi.org/10.1007/978-981-15-3308-2_6

Dao, Thi-Kien ; Chu, Shu-Chuan ; Pan, Jeng-Shyang et al. / An Improved Bat Algorithm Based on Hybrid with Ant Lion Optimizer. Genetic and Evolutionary Computing: Proceedings of the 13th International Conference on Genetic and Evolutionary Computing, 2019. editor / Jeng-Shyang Pan ; Jerry Chun-Wei Lin ; Yongquan Liang ; Shu-Chuan Chu. Singapore : Springer , 2020. pp. 50-60 (Advances in Intelligent Systems and Computing).

@inbook{9db1a0a2a16746a5a1e41cc8f38791a4,

title = "An Improved Bat Algorithm Based on Hybrid with Ant Lion Optimizer",

abstract = "Bat Algorithm (BA) is one of the fundamental algorithms for solving optimization problems. However, the BA still exists weaknesses in terms of exploitation and exploration. In this paper, an enhancing capability of exploration and exploitation for BA by hybridizing BA with Ant Lion Optimizer (ALO) is proposed for the global optimization problems. In the experimental section, several benchmark functions are used to test the performance of the proposed approach. Compared results with other algorithms literature show that the proposed method provides a new competitive algorithm.",

keywords = "Ant Lion Optimizer, Bat algorithm, Improved Bat algorithm, Optimization",

author = "Thi-Kien Dao and Shu-Chuan Chu and Jeng-Shyang Pan and Trong-The Nguyen and Truong-Giang Ngo and Trinh-Dong Nguyen and Huu-Trung Tran",

year = "2020",

month = jan,

day = "1",

doi = "10.1007/978-981-15-3308-2_6",

language = "English",

isbn = "9789811533075",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer ",

pages = "50--60",

editor = "Jeng-Shyang Pan and Lin, {Jerry Chun-Wei} and Yongquan Liang and Shu-Chuan Chu",

booktitle = "Genetic and Evolutionary Computing",

}

Dao, T-K, Chu, S-C, Pan, J-S, Nguyen, T-T, Ngo, T-G, Nguyen, T-D & Tran, H-T 2020, An Improved Bat Algorithm Based on Hybrid with Ant Lion Optimizer. in J-S Pan, JC-W Lin, Y Liang & S-C Chu (eds), Genetic and Evolutionary Computing: Proceedings of the 13th International Conference on Genetic and Evolutionary Computing, 2019. Advances in Intelligent Systems and Computing, vol. 1107 AISC, Springer , Singapore, pp. 50-60. https://doi.org/10.1007/978-981-15-3308-2_6

An Improved Bat Algorithm Based on Hybrid with Ant Lion Optimizer. / Dao, Thi-Kien; Chu, Shu-Chuan; Pan, Jeng-Shyang et al.
Genetic and Evolutionary Computing: Proceedings of the 13th International Conference on Genetic and Evolutionary Computing, 2019. ed. / Jeng-Shyang Pan; Jerry Chun-Wei Lin; Yongquan Liang; Shu-Chuan Chu. Singapore: Springer , 2020. p. 50-60 (Advances in Intelligent Systems and Computing; Vol. 1107 AISC).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - An Improved Bat Algorithm Based on Hybrid with Ant Lion Optimizer

AU - Dao, Thi-Kien

AU - Chu, Shu-Chuan

AU - Pan, Jeng-Shyang

AU - Nguyen, Trong-The

AU - Ngo, Truong-Giang

AU - Nguyen, Trinh-Dong

AU - Tran, Huu-Trung

PY - 2020/1/1

Y1 - 2020/1/1

N2 - Bat Algorithm (BA) is one of the fundamental algorithms for solving optimization problems. However, the BA still exists weaknesses in terms of exploitation and exploration. In this paper, an enhancing capability of exploration and exploitation for BA by hybridizing BA with Ant Lion Optimizer (ALO) is proposed for the global optimization problems. In the experimental section, several benchmark functions are used to test the performance of the proposed approach. Compared results with other algorithms literature show that the proposed method provides a new competitive algorithm.

AB - Bat Algorithm (BA) is one of the fundamental algorithms for solving optimization problems. However, the BA still exists weaknesses in terms of exploitation and exploration. In this paper, an enhancing capability of exploration and exploitation for BA by hybridizing BA with Ant Lion Optimizer (ALO) is proposed for the global optimization problems. In the experimental section, several benchmark functions are used to test the performance of the proposed approach. Compared results with other algorithms literature show that the proposed method provides a new competitive algorithm.

KW - Ant Lion Optimizer

KW - Bat algorithm

KW - Improved Bat algorithm

KW - Optimization

UR - http://www.scopus.com/inward/record.url?scp=85081990103&partnerID=8YFLogxK

U2 - 10.1007/978-981-15-3308-2_6

DO - 10.1007/978-981-15-3308-2_6

M3 - Chapter

SN - 9789811533075

T3 - Advances in Intelligent Systems and Computing

SP - 50

EP - 60

BT - Genetic and Evolutionary Computing

A2 - Pan, Jeng-Shyang

A2 - Lin, Jerry Chun-Wei

A2 - Liang, Yongquan

A2 - Chu, Shu-Chuan

PB - Springer

CY - Singapore

ER -

Dao TK, Chu SC, Pan JS, Nguyen TT, Ngo TG, Nguyen TD et al. An Improved Bat Algorithm Based on Hybrid with Ant Lion Optimizer. In Pan JS, Lin JCW, Liang Y, Chu SC, editors, Genetic and Evolutionary Computing: Proceedings of the 13th International Conference on Genetic and Evolutionary Computing, 2019. Singapore: Springer . 2020. p. 50-60. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-981-15-3308-2_6

An Improved Bat Algorithm Based on Hybrid with Ant Lion Optimizer

Abstract

Publication series

Keywords

Access to Document

Other files and links

Fingerprint

Cite this