Adaptive differential evolution for multi-objective optimization

Zai WANG; Zhenyu YANG; Ke TANG; Xin YAO

doi:10.1007/978-3-642-02298-2_2

Adaptive differential evolution for multi-objective optimization

Zai WANG, Zhenyu YANG, Ke TANG, Xin YAO

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

2 Citations (Scopus)

Abstract

No existing multi-objective evolutionary algorithms (MO-EAs) have ever been applied to problems with more than 1000 real-valued decision variables. Yet the real world is full of large and complex multi-objective problems. Motivated by the recent success of SaNSDE [1], an adaptive differential evolution algorithm that is capable of dealing with more than 1000 real-valued decision variables effectively and efficiently, this paper extends the ideas behind SaNSDE to develop a novel MOEA named MOSaNSDE. Our preliminary experimental studies have shown that MOSaNSDE outperforms state-of-the-art MOEAs significantly on most problems we have tested, in terms of both convergence and diversity metrics. Such encouraging results call for a more in-depth study of MOSaNSDE in the future, especially about its scalability. © 2009 Springer Berlin Heidelberg.

Original language	English
Title of host publication	Cutting-Edge Research Topics on Multiple Criteria Decision Making : 20th International Conference, MCDM 2009, Chengdu/Jiuzhaigou, China, June 21-26, 2009. Proceedings
Editors	Yong SHI, Shouyang WANG, Yi PENG, Jianping LI, Yong ZENG
Publisher	Springer Berlin Heidelberg
Pages	9-16
Number of pages	8
ISBN (Electronic)	9783642022982
ISBN (Print)	9783642022975
DOIs	https://doi.org/10.1007/978-3-642-02298-2_2
Publication status	Published - 2009
Externally published	Yes
Event	20th International Conference on Multiple Criteria Decision Makin, MCDM 2009 - Chengdu, China Duration: 21 Jun 2009 → 26 Jun 2009

Publication series

Name	Communications in Computer and Information Science
Publisher	Springer Berlin, Heidelberg
Volume	35
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	20th International Conference on Multiple Criteria Decision Makin, MCDM 2009
Country/Territory	China
City	Chengdu
Period	21/06/09 → 26/06/09

Funding

This work is partially supported by the National Natural Science Foundation of China (Grant No. 60428202), The Fund for Foreign Scholars in University Research and Teaching Programs (Grant No. B07033) and an EPSRC Grant (EP/D052785/1) on “SEBASE: Software Engineering By Automated SEarch”.

Keywords

Particle Swarm Optimization
Multiobjective Optimization
Nondominated Solution
External Archive
Pareto Archive Evolution Strategy

Access to Document

10.1007/978-3-642-02298-2_2

Cite this

WANG, Z., YANG, Z., TANG, K., & YAO, X. (2009). Adaptive differential evolution for multi-objective optimization. In Y. SHI, S. WANG, Y. PENG, J. LI, & Y. ZENG (Eds.), Cutting-Edge Research Topics on Multiple Criteria Decision Making : 20th International Conference, MCDM 2009, Chengdu/Jiuzhaigou, China, June 21-26, 2009. Proceedings (pp. 9-16). (Communications in Computer and Information Science; Vol. 35). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-02298-2_2

WANG, Zai ; YANG, Zhenyu ; TANG, Ke et al. / Adaptive differential evolution for multi-objective optimization. Cutting-Edge Research Topics on Multiple Criteria Decision Making : 20th International Conference, MCDM 2009, Chengdu/Jiuzhaigou, China, June 21-26, 2009. Proceedings. editor / Yong SHI ; Shouyang WANG ; Yi PENG ; Jianping LI ; Yong ZENG. Springer Berlin Heidelberg, 2009. pp. 9-16 (Communications in Computer and Information Science).

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title = "Adaptive differential evolution for multi-objective optimization",

abstract = "No existing multi-objective evolutionary algorithms (MO-EAs) have ever been applied to problems with more than 1000 real-valued decision variables. Yet the real world is full of large and complex multi-objective problems. Motivated by the recent success of SaNSDE [1], an adaptive differential evolution algorithm that is capable of dealing with more than 1000 real-valued decision variables effectively and efficiently, this paper extends the ideas behind SaNSDE to develop a novel MOEA named MOSaNSDE. Our preliminary experimental studies have shown that MOSaNSDE outperforms state-of-the-art MOEAs significantly on most problems we have tested, in terms of both convergence and diversity metrics. Such encouraging results call for a more in-depth study of MOSaNSDE in the future, especially about its scalability. {\textcopyright} 2009 Springer Berlin Heidelberg.",

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author = "Zai WANG and Zhenyu YANG and Ke TANG and Xin YAO",

year = "2009",

doi = "10.1007/978-3-642-02298-2_2",

language = "English",

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booktitle = "Cutting-Edge Research Topics on Multiple Criteria Decision Making : 20th International Conference, MCDM 2009, Chengdu/Jiuzhaigou, China, June 21-26, 2009. Proceedings",

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WANG, Z, YANG, Z, TANG, K & YAO, X 2009, Adaptive differential evolution for multi-objective optimization. in Y SHI, S WANG, Y PENG, J LI & Y ZENG (eds), Cutting-Edge Research Topics on Multiple Criteria Decision Making : 20th International Conference, MCDM 2009, Chengdu/Jiuzhaigou, China, June 21-26, 2009. Proceedings. Communications in Computer and Information Science, vol. 35, Springer Berlin Heidelberg, pp. 9-16, 20th International Conference on Multiple Criteria Decision Makin, MCDM 2009, Chengdu, China, 21/06/09. https://doi.org/10.1007/978-3-642-02298-2_2

Adaptive differential evolution for multi-objective optimization. / WANG, Zai; YANG, Zhenyu; TANG, Ke et al.
Cutting-Edge Research Topics on Multiple Criteria Decision Making : 20th International Conference, MCDM 2009, Chengdu/Jiuzhaigou, China, June 21-26, 2009. Proceedings. ed. / Yong SHI; Shouyang WANG; Yi PENG; Jianping LI; Yong ZENG. Springer Berlin Heidelberg, 2009. p. 9-16 (Communications in Computer and Information Science; Vol. 35).

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

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AU - YANG, Zhenyu

AU - TANG, Ke

AU - YAO, Xin

PY - 2009

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N2 - No existing multi-objective evolutionary algorithms (MO-EAs) have ever been applied to problems with more than 1000 real-valued decision variables. Yet the real world is full of large and complex multi-objective problems. Motivated by the recent success of SaNSDE [1], an adaptive differential evolution algorithm that is capable of dealing with more than 1000 real-valued decision variables effectively and efficiently, this paper extends the ideas behind SaNSDE to develop a novel MOEA named MOSaNSDE. Our preliminary experimental studies have shown that MOSaNSDE outperforms state-of-the-art MOEAs significantly on most problems we have tested, in terms of both convergence and diversity metrics. Such encouraging results call for a more in-depth study of MOSaNSDE in the future, especially about its scalability. © 2009 Springer Berlin Heidelberg.

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BT - Cutting-Edge Research Topics on Multiple Criteria Decision Making : 20th International Conference, MCDM 2009, Chengdu/Jiuzhaigou, China, June 21-26, 2009. Proceedings

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ER -

WANG Z, YANG Z, TANG K, YAO X. Adaptive differential evolution for multi-objective optimization. In SHI Y, WANG S, PENG Y, LI J, ZENG Y, editors, Cutting-Edge Research Topics on Multiple Criteria Decision Making : 20th International Conference, MCDM 2009, Chengdu/Jiuzhaigou, China, June 21-26, 2009. Proceedings. Springer Berlin Heidelberg. 2009. p. 9-16. (Communications in Computer and Information Science). doi: 10.1007/978-3-642-02298-2_2

Adaptive differential evolution for multi-objective optimization

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