Dynamic Multimodal Optimization: A Preliminary Study

Shi Cheng; Hui Lu; Yi Nan Guo; Xiujuan Lei; Jing Liang; Junfeng Chen; Yuhui Shi

doi:10.1109/CEC.2019.8790078

Dynamic Multimodal Optimization: A Preliminary Study

Shi Cheng
, Hui Lu
, Yi Nan Guo
, Xiujuan Lei
, Jing Liang
, Junfeng Chen
, Yuhui Shi

电子信息工程学院

Shaanxi Normal University
China University of Mining and Technology
Zhengzhou University
Hohai University Changzhou
Southern University of Science and Technology

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

11 引用（Scopus）

摘要

The benchmark problems have played a fundamental role in verifying the algorithm's search ability. A dynamic multimodal optimization (DMO) problem is defined as an optimization problem with multiple global optima and characteristics of global optima which are changed during the search process. Two cases are used to illustrate the application scenario of DMO. A set of benchmark functions on DMO, which contains eight problems, are proposed to show the difficulty of DMO. The properties of the proposed benchmark problems, such as the distribution of solutions, the scalability, the number of global/local optima, are discussed.

源语言	英语
主期刊名	2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings
出版商	Institute of Electrical and Electronics Engineers Inc.
页	279-285
页数	7
ISBN（电子版）	9781728121536
DOI	https://doi.org/10.1109/CEC.2019.8790078
出版状态	已出版 - 6月 2019
活动	2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Wellington, 新西兰期限: 10 6月 2019 → 13 6月 2019

出版系列

姓名	2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings

会议

会议	2019 IEEE Congress on Evolutionary Computation, CEC 2019
国家/地区	新西兰
市	Wellington
时期	10/06/19 → 13/06/19

访问文件

10.1109/CEC.2019.8790078

其它文件与链接

链接到 Scopus 的出版物

引用此

Cheng, S., Lu, H., Guo, Y. N., Lei, X., Liang, J., Chen, J., & Shi, Y. (2019). Dynamic Multimodal Optimization: A Preliminary Study. 在 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (页码 279-285). 文章 8790078 (2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2019.8790078

@inproceedings{cf9fe15f9f4249728cd564ae2dc5b7e7,

title = "Dynamic Multimodal Optimization: A Preliminary Study",

abstract = "The benchmark problems have played a fundamental role in verifying the algorithm's search ability. A dynamic multimodal optimization (DMO) problem is defined as an optimization problem with multiple global optima and characteristics of global optima which are changed during the search process. Two cases are used to illustrate the application scenario of DMO. A set of benchmark functions on DMO, which contains eight problems, are proposed to show the difficulty of DMO. The properties of the proposed benchmark problems, such as the distribution of solutions, the scalability, the number of global/local optima, are discussed.",

keywords = "Benchmark functions, Dynamic multimodal optimization, Dynamic multimodal optimization problem, Swarm intelligence",

author = "Shi Cheng and Hui Lu and Guo, \{Yi Nan\} and Xiujuan Lei and Jing Liang and Junfeng Chen and Yuhui Shi",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE Congress on Evolutionary Computation, CEC 2019 ; Conference date: 10-06-2019 Through 13-06-2019",

year = "2019",

month = jun,

doi = "10.1109/CEC.2019.8790078",

language = "英语",

series = "2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings",

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

pages = "279--285",

booktitle = "2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings",

address = "美国",

}

Cheng, S, Lu, H, Guo, YN, Lei, X, Liang, J, Chen, J & Shi, Y 2019, Dynamic Multimodal Optimization: A Preliminary Study. 在 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings., 8790078, 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 页码 279-285, 2019 IEEE Congress on Evolutionary Computation, CEC 2019, Wellington, 新西兰, 10/06/19. https://doi.org/10.1109/CEC.2019.8790078

Dynamic Multimodal Optimization: A Preliminary Study. / Cheng, Shi; Lu, Hui; Guo, Yi Nan 等.
2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 页码 279-285 8790078 (2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Dynamic Multimodal Optimization

T2 - 2019 IEEE Congress on Evolutionary Computation, CEC 2019

AU - Cheng, Shi

AU - Lu, Hui

AU - Guo, Yi Nan

AU - Lei, Xiujuan

AU - Liang, Jing

AU - Chen, Junfeng

AU - Shi, Yuhui

PY - 2019/6

Y1 - 2019/6

N2 - The benchmark problems have played a fundamental role in verifying the algorithm's search ability. A dynamic multimodal optimization (DMO) problem is defined as an optimization problem with multiple global optima and characteristics of global optima which are changed during the search process. Two cases are used to illustrate the application scenario of DMO. A set of benchmark functions on DMO, which contains eight problems, are proposed to show the difficulty of DMO. The properties of the proposed benchmark problems, such as the distribution of solutions, the scalability, the number of global/local optima, are discussed.

AB - The benchmark problems have played a fundamental role in verifying the algorithm's search ability. A dynamic multimodal optimization (DMO) problem is defined as an optimization problem with multiple global optima and characteristics of global optima which are changed during the search process. Two cases are used to illustrate the application scenario of DMO. A set of benchmark functions on DMO, which contains eight problems, are proposed to show the difficulty of DMO. The properties of the proposed benchmark problems, such as the distribution of solutions, the scalability, the number of global/local optima, are discussed.

KW - Benchmark functions

KW - Dynamic multimodal optimization

KW - Dynamic multimodal optimization problem

KW - Swarm intelligence

UR - https://www.scopus.com/pages/publications/85071309890

U2 - 10.1109/CEC.2019.8790078

DO - 10.1109/CEC.2019.8790078

M3 - 会议稿件

AN - SCOPUS:85071309890

T3 - 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings

SP - 279

EP - 285

BT - 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 10 June 2019 through 13 June 2019

ER -

Cheng S, Lu H, Guo YN, Lei X, Liang J, Chen J 等. Dynamic Multimodal Optimization: A Preliminary Study. 在 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. 页码 279-285. 8790078. (2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings). doi: 10.1109/CEC.2019.8790078

Dynamic Multimodal Optimization: A Preliminary Study

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