| Title | Dynamic Multi-modal Multi-objective Optimization: A Preliminary Study |
| Author | |
| Corresponding Author | Ishibuchi，Hisao |
| DOI | |
| Publication Years | 2022
|
| Conference Name | 17th International Conference on Parallel Problem Solving from Nature (PPSN)
|
| ISSN | 0302-9743
|
| EISSN | 1611-3349
|
| ISBN | 978-3-031-14720-3
|
| Source Title | |
| Volume | 13399 LNCS
|
| Pages | 138-150
|
| Conference Date | SEP 10-14, 2022
|
| Conference Place | null,Dortmund,GERMANY
|
| Publication Place | GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
|
| Publisher | |
| Abstract | Many real-world multi-modal multi-objective optimization problems are subject to continuously changing environments, which requires the optimizer to track multiple equivalent Pareto sets in the decision space. To the best of our knowledge, this type of optimization problems has not been studied in the literature. To fill the research gap in this area, we provide a preliminary study on dynamic multi-modal multi-objective optimization. We give a formal definition of dynamic multi-modal multi-objective optimization problems and point out some key challenges in solving them. To facilitate algorithm development, we suggest a systematic approach to construct benchmark problems. Furthermore, we provide a feature-rich test suite containing 10 novel dynamic multi-modal multi-objective test problems. |
| Keywords | |
| SUSTech Authorship | First
; Corresponding
|
| Language | English
|
| URL | [Source Record] |
| Indexed By | |
| Funding Project | National Natural Science Foundation of China[61876075]
; Guangdong Provincial Key Laboratory[2020B121201001]
; Program for Guangdong Introducing Innovative and Entrepreneurial Teams[2017ZT07X386]
; Stable Support Plan Program of Shenzhen Natural Science Fund[20200925174447003]
; Shenzhen Science and Technology Program[KQTD2016112514355531]
|
| WOS Research Area | Computer Science
|
| WOS Subject | Computer Science, Artificial Intelligence
|
| WOS Accession No | WOS:000871753400010
|
| EI Accession Number | 20223712707320
|
| EI Keywords | Benchmarking
|
| ESI Classification Code | Optimization Techniques:921.5
|
| Scopus EID | 2-s2.0-85137261296
|
| Data Source | Scopus
|
| Citation statistics |
Cited Times [WOS]:0
|
| Document Type | Conference paper |
| Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/401664 |
| Department | Department of Computer Science and Engineering |
| Affiliation | Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation,Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China |
| First Author Affilication | Department of Computer Science and Engineering |
| Corresponding Author Affilication | Department of Computer Science and Engineering |
| First Author's First Affilication | Department of Computer Science and Engineering |
| Recommended Citation GB/T 7714 |
Peng，Yiming,Ishibuchi，Hisao. Dynamic Multi-modal Multi-objective Optimization: A Preliminary Study[C]. GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND:SPRINGER INTERNATIONAL PUBLISHING AG,2022:138-150.
|
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