A Negatively Correlation-Based Selection Strategy for Parameter Adaptation in SHADE

Yanting Liu; Houtian He; Zhe Wang; Zesheng Zhang; Zhe Xu; Shangce Gao

doi:10.1109/ISCID.2019.00048

A Negatively Correlation-Based Selection Strategy for Parameter Adaptation in SHADE

Yanting Liu, Houtian He, Zhe Wang, Zesheng Zhang, Zhe Xu, Shangce Gao

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

Abstract

Negatively correlated search (NCS) is a population-based metaheuristic algorithm inspired by human behaviors in cooperation. One of the main processes of NCS is to evaluate the Bhattacharyya distance of two generations of population and employ a 'winner takes all' selection strategy to possess good exploitation ability. SHADE is an efficient variant of differential evolution algorithm which embedded a success-history based parameter adaptation strategy and demonstrates strong exploration capability. In this paper, a simple hybridization of NCS and SHADE is presented, which employs the negatively correlated method in the selection strategy of success parameters of SHADE. Due to the combination of advantages of both algorithms, the newly proposed NC-SHADE performs excellently on CEC'2017 benchmark function suit and has superiority in comparison with other related algorithms.

Original language	English
Title of host publication	Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	180-184
Number of pages	5
ISBN (Electronic)	9781728146522
DOIs	https://doi.org/10.1109/ISCID.2019.00048
State	Published - 2019/12
Event	12th International Symposium on Computational Intelligence and Design, ISCID 2019 - Hangzhou, China Duration: 2019/12/14 → 2019/12/15

Publication series

Name	Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019
Volume	1

Conference

Conference	12th International Symposium on Computational Intelligence and Design, ISCID 2019
Country/Territory	China
City	Hangzhou
Period	2019/12/14 → 2019/12/15

Keywords

Bhattacharyya distance
Negatively correlated search
differential evolution
parameter adaptation
selection strategy

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Hardware and Architecture
Information Systems and Management
Control and Optimization

Access to Document

10.1109/ISCID.2019.00048

Cite this

Liu, Y., He, H., Wang, Z., Zhang, Z., Xu, Z., & Gao, S. (2019). A Negatively Correlation-Based Selection Strategy for Parameter Adaptation in SHADE. In Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019 (pp. 180-184). Article 9098290 (Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019; Vol. 1). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCID.2019.00048

Liu, Yanting ; He, Houtian ; Wang, Zhe et al. / A Negatively Correlation-Based Selection Strategy for Parameter Adaptation in SHADE. Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 180-184 (Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019).

@inproceedings{be1d222d30be439a866f1d5728bb1d59,

title = "A Negatively Correlation-Based Selection Strategy for Parameter Adaptation in SHADE",

abstract = "Negatively correlated search (NCS) is a population-based metaheuristic algorithm inspired by human behaviors in cooperation. One of the main processes of NCS is to evaluate the Bhattacharyya distance of two generations of population and employ a 'winner takes all' selection strategy to possess good exploitation ability. SHADE is an efficient variant of differential evolution algorithm which embedded a success-history based parameter adaptation strategy and demonstrates strong exploration capability. In this paper, a simple hybridization of NCS and SHADE is presented, which employs the negatively correlated method in the selection strategy of success parameters of SHADE. Due to the combination of advantages of both algorithms, the newly proposed NC-SHADE performs excellently on CEC'2017 benchmark function suit and has superiority in comparison with other related algorithms.",

keywords = "Bhattacharyya distance, Negatively correlated search, differential evolution, parameter adaptation, selection strategy",

author = "Yanting Liu and Houtian He and Zhe Wang and Zesheng Zhang and Zhe Xu and Shangce Gao",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 12th International Symposium on Computational Intelligence and Design, ISCID 2019 ; Conference date: 14-12-2019 Through 15-12-2019",

year = "2019",

month = dec,

doi = "10.1109/ISCID.2019.00048",

language = "英語",

series = "Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019",

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

pages = "180--184",

booktitle = "Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019",

}

Liu, Y, He, H, Wang, Z, Zhang, Z, Xu, Z & Gao, S 2019, A Negatively Correlation-Based Selection Strategy for Parameter Adaptation in SHADE. in Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019., 9098290, Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019, vol. 1, Institute of Electrical and Electronics Engineers Inc., pp. 180-184, 12th International Symposium on Computational Intelligence and Design, ISCID 2019, Hangzhou, China, 2019/12/14. https://doi.org/10.1109/ISCID.2019.00048

A Negatively Correlation-Based Selection Strategy for Parameter Adaptation in SHADE. / Liu, Yanting; He, Houtian; Wang, Zhe et al.
Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 180-184 9098290 (Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019; Vol. 1).

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

TY - GEN

T1 - A Negatively Correlation-Based Selection Strategy for Parameter Adaptation in SHADE

AU - Liu, Yanting

AU - He, Houtian

AU - Wang, Zhe

AU - Zhang, Zesheng

AU - Xu, Zhe

AU - Gao, Shangce

PY - 2019/12

Y1 - 2019/12

N2 - Negatively correlated search (NCS) is a population-based metaheuristic algorithm inspired by human behaviors in cooperation. One of the main processes of NCS is to evaluate the Bhattacharyya distance of two generations of population and employ a 'winner takes all' selection strategy to possess good exploitation ability. SHADE is an efficient variant of differential evolution algorithm which embedded a success-history based parameter adaptation strategy and demonstrates strong exploration capability. In this paper, a simple hybridization of NCS and SHADE is presented, which employs the negatively correlated method in the selection strategy of success parameters of SHADE. Due to the combination of advantages of both algorithms, the newly proposed NC-SHADE performs excellently on CEC'2017 benchmark function suit and has superiority in comparison with other related algorithms.

AB - Negatively correlated search (NCS) is a population-based metaheuristic algorithm inspired by human behaviors in cooperation. One of the main processes of NCS is to evaluate the Bhattacharyya distance of two generations of population and employ a 'winner takes all' selection strategy to possess good exploitation ability. SHADE is an efficient variant of differential evolution algorithm which embedded a success-history based parameter adaptation strategy and demonstrates strong exploration capability. In this paper, a simple hybridization of NCS and SHADE is presented, which employs the negatively correlated method in the selection strategy of success parameters of SHADE. Due to the combination of advantages of both algorithms, the newly proposed NC-SHADE performs excellently on CEC'2017 benchmark function suit and has superiority in comparison with other related algorithms.

KW - Bhattacharyya distance

KW - Negatively correlated search

KW - differential evolution

KW - parameter adaptation

KW - selection strategy

UR - http://www.scopus.com/inward/record.url?scp=85089440693&partnerID=8YFLogxK

U2 - 10.1109/ISCID.2019.00048

DO - 10.1109/ISCID.2019.00048

M3 - 会議への寄与

AN - SCOPUS:85089440693

T3 - Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019

SP - 180

EP - 184

BT - Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 12th International Symposium on Computational Intelligence and Design, ISCID 2019

Y2 - 14 December 2019 through 15 December 2019

ER -

Liu Y, He H, Wang Z, Zhang Z, Xu Z, Gao S. A Negatively Correlation-Based Selection Strategy for Parameter Adaptation in SHADE. In Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 180-184. 9098290. (Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019). doi: 10.1109/ISCID.2019.00048

A Negatively Correlation-Based Selection Strategy for Parameter Adaptation in SHADE

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this