An Efficient Negative Correlation Gravitational Search Algorithm

Huiqin Chen; Qianyi Peng; Xiaosi Li; Yuki Todo; Shangce Gao

doi:10.1109/PIC.2018.8706274

An Efficient Negative Correlation Gravitational Search Algorithm

Huiqin Chen, Qianyi Peng, Xiaosi Li, Yuki Todo, Shangce Gao^*

^*Corresponding author for this work

Intellectual Information Engineering

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

3 Scopus citations

Abstract

Gravitational search algorithm (GSA) is known as an effective optimization algorithm based on population. To further improve the performance of GSA, taking the combination of diversified search mechanisms into consideration would be a constructive solution for increasing the possibility of obtaining global optimum. In the meantime, the negative correlation search (NCS) algorithm has proven its ability of maintaining diversity effectively to develop the population. Thus, with such inspiration, an improved gravitational search algorithm based on negative correlation learning is proposed in this paper. While gravitational search conducts exploitation in the search space, negative correlation fulfills exploration by encouraging discrepant search behaviors to increase the optimization accuracy. The superiority of the proposed algorithm is demonstrated with experimental results based on several benchmark functions in comparison with its component algorithms.

Original language	English
Title of host publication	Proceedings of the 2018 IEEE International Conference on Progress in Informatics and Computing, PIC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	73-79
Number of pages	7
ISBN (Electronic)	9781538676707
DOIs	https://doi.org/10.1109/PIC.2018.8706274
State	Published - 2018/07/02
Event	6th IEEE International Conference on Progress in Informatics and Computing, PIC 2018 - Suzhou, China Duration: 2018/12/14 → 2018/12/16

Publication series

Name	Proceedings of the 2018 IEEE International Conference on Progress in Informatics and Computing, PIC 2018

Conference

Conference	6th IEEE International Conference on Progress in Informatics and Computing, PIC 2018
Country/Territory	China
City	Suzhou
Period	2018/12/14 → 2018/12/16

Keywords

computational intelligence
gravitational search algorithm
hybridization
negative correlation learning
optimization

ASJC Scopus subject areas

Language and Linguistics
Linguistics and Language

Access to Document

10.1109/PIC.2018.8706274

Cite this

Chen, H., Peng, Q., Li, X., Todo, Y., & Gao, S. (2018). An Efficient Negative Correlation Gravitational Search Algorithm. In Proceedings of the 2018 IEEE International Conference on Progress in Informatics and Computing, PIC 2018 (pp. 73-79). Article 8706274 (Proceedings of the 2018 IEEE International Conference on Progress in Informatics and Computing, PIC 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PIC.2018.8706274

Chen, Huiqin ; Peng, Qianyi ; Li, Xiaosi et al. / An Efficient Negative Correlation Gravitational Search Algorithm. Proceedings of the 2018 IEEE International Conference on Progress in Informatics and Computing, PIC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 73-79 (Proceedings of the 2018 IEEE International Conference on Progress in Informatics and Computing, PIC 2018).

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title = "An Efficient Negative Correlation Gravitational Search Algorithm",

abstract = "Gravitational search algorithm (GSA) is known as an effective optimization algorithm based on population. To further improve the performance of GSA, taking the combination of diversified search mechanisms into consideration would be a constructive solution for increasing the possibility of obtaining global optimum. In the meantime, the negative correlation search (NCS) algorithm has proven its ability of maintaining diversity effectively to develop the population. Thus, with such inspiration, an improved gravitational search algorithm based on negative correlation learning is proposed in this paper. While gravitational search conducts exploitation in the search space, negative correlation fulfills exploration by encouraging discrepant search behaviors to increase the optimization accuracy. The superiority of the proposed algorithm is demonstrated with experimental results based on several benchmark functions in comparison with its component algorithms.",

keywords = "computational intelligence, gravitational search algorithm, hybridization, negative correlation learning, optimization",

author = "Huiqin Chen and Qianyi Peng and Xiaosi Li and Yuki Todo and Shangce Gao",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 6th IEEE International Conference on Progress in Informatics and Computing, PIC 2018 ; Conference date: 14-12-2018 Through 16-12-2018",

year = "2018",

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doi = "10.1109/PIC.2018.8706274",

language = "英語",

series = "Proceedings of the 2018 IEEE International Conference on Progress in Informatics and Computing, PIC 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Chen, H, Peng, Q, Li, X, Todo, Y & Gao, S 2018, An Efficient Negative Correlation Gravitational Search Algorithm. in Proceedings of the 2018 IEEE International Conference on Progress in Informatics and Computing, PIC 2018., 8706274, Proceedings of the 2018 IEEE International Conference on Progress in Informatics and Computing, PIC 2018, Institute of Electrical and Electronics Engineers Inc., pp. 73-79, 6th IEEE International Conference on Progress in Informatics and Computing, PIC 2018, Suzhou, China, 2018/12/14. https://doi.org/10.1109/PIC.2018.8706274

An Efficient Negative Correlation Gravitational Search Algorithm. / Chen, Huiqin; Peng, Qianyi; Li, Xiaosi et al.
Proceedings of the 2018 IEEE International Conference on Progress in Informatics and Computing, PIC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 73-79 8706274 (Proceedings of the 2018 IEEE International Conference on Progress in Informatics and Computing, PIC 2018).

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

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AU - Li, Xiaosi

AU - Todo, Yuki

AU - Gao, Shangce

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Y1 - 2018/7/2

N2 - Gravitational search algorithm (GSA) is known as an effective optimization algorithm based on population. To further improve the performance of GSA, taking the combination of diversified search mechanisms into consideration would be a constructive solution for increasing the possibility of obtaining global optimum. In the meantime, the negative correlation search (NCS) algorithm has proven its ability of maintaining diversity effectively to develop the population. Thus, with such inspiration, an improved gravitational search algorithm based on negative correlation learning is proposed in this paper. While gravitational search conducts exploitation in the search space, negative correlation fulfills exploration by encouraging discrepant search behaviors to increase the optimization accuracy. The superiority of the proposed algorithm is demonstrated with experimental results based on several benchmark functions in comparison with its component algorithms.

AB - Gravitational search algorithm (GSA) is known as an effective optimization algorithm based on population. To further improve the performance of GSA, taking the combination of diversified search mechanisms into consideration would be a constructive solution for increasing the possibility of obtaining global optimum. In the meantime, the negative correlation search (NCS) algorithm has proven its ability of maintaining diversity effectively to develop the population. Thus, with such inspiration, an improved gravitational search algorithm based on negative correlation learning is proposed in this paper. While gravitational search conducts exploitation in the search space, negative correlation fulfills exploration by encouraging discrepant search behaviors to increase the optimization accuracy. The superiority of the proposed algorithm is demonstrated with experimental results based on several benchmark functions in comparison with its component algorithms.

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Chen H, Peng Q, Li X, Todo Y, Gao S. An Efficient Negative Correlation Gravitational Search Algorithm. In Proceedings of the 2018 IEEE International Conference on Progress in Informatics and Computing, PIC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 73-79. 8706274. (Proceedings of the 2018 IEEE International Conference on Progress in Informatics and Computing, PIC 2018). doi: 10.1109/PIC.2018.8706274

An Efficient Negative Correlation Gravitational Search Algorithm

Abstract

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Keywords

ASJC Scopus subject areas

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